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Basic Recommender Systems

3,448

4.3

Paolo Cremonesi

EIT Digital

[]

The Basic Recommender Systems course introduces you to the leading approaches in recommender systems. The techniques described touch both collaborative and content-based approaches and include the most important algorithms used to provide recommendations. You'll learn how they work, how to use and how to evaluate them, pointing out benefits and limits of different recommender system alternatives. After completing this course, you'll be able to describe the requirements and objectives of recommender systems based on different application domains. You'll know how to distinguish recommender systems according to their input data, their internal working mechanisms, and their goals. You’ll have the tools to measure the quality of a recommender system and incrementally improve it with the design of new algorithms. You'll learn as well how to design recommender systems tailored for new application domains, also considering surrounding social and ethical issues such as identity, privacy, and manipulation. Providing affordable, personalised and high-quality recommendations is always a challenge! The course also leverages two important EIT Overarching Learning Outcomes (OLOs), related to creativity and innovation skills. In trying to design a new recommender system you need to think beyond boundaries and try to figure out how you can improve the quality of the predictions. You should also be able to use knowledge, ideas and technology to create new or significantly improved recommendation tools to support choice-making processes and strategies in different and innovative scenarios, for a better quality of life. In this first module, we'll review the basic concepts for recommender systems in order to classify and analyse different families of algorithms, related to specific set of input data. At the end, you’ll be able to choose the most suitable type of algorithm based on the data available, your needs and goals. Conversely, you'll know how to select the input data based on the algorithm you want to use. 11 videos2 readings1 assignment1 peer review2 discussion prompts In this second module, we'll learn how to define and measure the quality of a recommender system. We'll review different metrics that can be used to measure for this purpose. At the end of the module you'll be able to identify the correct evaluation activities required to measure the quality of a given recommender system, based on goals and needs. 12 videos1 assignment1 peer review2 discussion prompts In this module we’ll analyse content-based recommender techniques. These algorithms recommend items similar to the ones a user liked in the past. We’ll review different similarity functions and you’ll then be able to choose the more suitable one for your system. The main input is the Item-Content Matrix (ICM) which describes all the attributes for each item. We’ll see how we can improve the quality of content-based techniques, by normalising and tuning the importance of each attribute in the ICM: you’ll be able to use some specific tuning strategies in order to obtain the best quality recommendations from your system. So, at the end of this module, you’ll know how to build a content-based recommender system, how to clean and normalize your input data. 9 videos1 assignment1 peer review2 discussion prompts In this module we’ll study collaborative filtering techniques, which use the User Rating Matrix (URM) as the main input data, describing the interaction between users and items. We’ll learn how to build non-personalised recommender systems and how to normalise the URM, in order to provide better recommendations. At the end of the module you’ll be able to select the most appropriate similarity function and the most suitable way to compute similarity, overcoming issues related to explicit ratings. 9 videos1 assignment1 peer review2 discussion prompts

4 modules

Intermediate level

11 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/basic-recommender-systems

Intel® Technical Pro – Intel® Gaudi® AI Accelerator

Enrollment number not found

Rating not found

Jennifer James

Intel

['Deep Learning', 'AI Workload', 'Artificial Intelligence', 'AI processes']

This competency provides a comprehensive overview of the Intel® Gaudi® AI accelerator. Addressed will be the cost-effectiveness of Intel® Gaudi® AI accelerator, its scalability and an overview of the new Intel® Gaudi® 2 AI accelerator hardware and software architecture including rack-level integrations. This course provides an in-depth exploration of the Intel® Gaudi® AI accelerator on Amazon Web Service's deep learning training product. It includes practical insights into cost comparisons that demonstrate the cost-effectiveness of Intel® Gaudi® AI Accelerator. You'll also gain a thorough understanding of Gaudi's scalability. In the lab, you will migrate the TensorFlow EfficientNet workload to utilize the power of the Intel® Gaudi® AI accelerator, demonstrating how it supercharges your AI workload and significantly reduces processing time. 1 reading1 assignment2 plugins This course will provide an overview of the Intel® Gaudi® AI accelerator hardware and software architecture. The course will cover the model migration from a graphics processing unit (GPU) to the Intel® Gaudi® AI accelerator. The course will also discuss rack-level integrations. 1 assignment3 plugins

2 modules

Intermediate level

2 hours to complete

https://www.coursera.org/learn/intel-technical-pro-gaudi-ai-accelerator

Learn to Teach Java: Sequences, Primitive Types and Using Objects

4,722

4.9

Beth Simon

University of California San Diego

['Computer Programming', 'Teaching', 'Java', 'APCS A', 'Objects']

Get started with the basics of Java, and prepare to teach others using the free, online interactive CS Awesome textbook. In this course for teachers we'll guide you both in learning Java concepts and skills but also in how to effectively teach those to your students. This course will support you in teaching the Advanced Placement Computer Science A course or a similar introductory university-level programming course. We'll begin with simple instruction sequences, primitive types, and using objects, as covered in the APCS A Units 1 and 2. Each topic will begin by relating Java to block-based programming languages and then provide video overviews of CS Awesome content along with additional materials to supplement learning for your students. You'll engage with additional materials to support your teaching including "deep dive" classroom discussion questions and assessment overviews and options for your students. Meet Dr. Simon and fellow learners in this class! Find out what you’ll be doing and learning. 2 videos2 readings1 discussion prompt Instructions are the basic building blocks for programs. The sentences in our "essay", if you will (not a popular analogy for students - but true). Using CS Awesome, we'll learn some basic instructions in Java -- which focus more on storing and manipulating data (numbers and words) than we did in most block-based programming languages. 6 videos3 readings3 assignments1 discussion prompt This week we'll go deeper and engage with some resources to support your teaching. You'll explore some questions to use in classroom analysis discussions (Peer Instruction), learn how these concepts are commonly assessed, and prepare to help students who are having trouble with CS Awesome assessments. Finally, you can check your own Unit 1 Java and Java Teacher mastery on our end of Unit 1 quizzes. 7 videos2 readings2 assignments1 app item One of the key features of Java (as well as some other modern programming languages) is that it is "object-oriented" -- that we can design programs based around modeling of objects as a combination of data and methods (or actions) on that data. Using CS Awesome, we'll learn how to use already defined classes (classes are types of objects), to increase our power in solving problems in Java. 16 videos1 reading7 assignments This week we'll go deeper and engage with some resources to support your teaching. You'll explore some questions to use in classroom analysis discussions (Peer Instruction), learn how these concepts are commonly assessed, and prepare to help students who are having trouble with CS Awesome assessments. Finally, you can check your own Unit 2 Java and Java Teacher mastery on our end of Unit 2 quizzes. 4 videos2 assignments1 app item

5 modules

Beginner level

13 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/teach-java-sequences-primitive-types-object

Basic System Programming on IBM Z

9,953

4.8

Jeff Bisti

IBM

['JCL', 'System Programming', 'System Administration', 'Unix', 'DB2']

The foundational knowledge for the position of an IBM z/OS System Programmer and System Administrator begins with this third and final course in the three course professional certificate track. This course provides hands-on labs to everyday z/OS tasks with JCL, JES, ISHELL and HFS, and z/OSMF. Topics covered include VSAM, z/OS System Libraries, the Language Environment, Generation Data Groups, RAIM, DB2, UNIX System Services, and USS File System. On successful completion of this course, the learners are eligible to claim the Basic System Programming on IBM Z badge. More information can be found here : https://www.youracclaim.com/org/ibm/badge/basic-system-programming-on-ibm-z 8 videos2 readings8 assignments4 plugins 10 videos1 reading7 assignments 7 videos1 reading6 assignments2 plugins

3 modules

Intermediate level

18 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/system-programming

Skills for Working as an AWS Cloud Consultant

3,404

4.8

Alex G.

Amazon Web Services

['Management', 'strategy', 'Implementation', 'Troubleshooting', 'Migration']

Being a successful cloud consultant is finding the balance of soft skills and hard skills when investigating and solving customer problems. This course is designed to improve students’ understanding of key soft skills necessary to become successful cloud consultants. The course's first week provides foundational knowledge of what cloud consulting is and then dives into important skills for solving customers’ business problems. During the second week, students learn how to work with customers (gather requirements, propose a solution, plan and build out the project, monitor progress, and conclude final tasks) and how different soft skills can help them throughout all stages of the process. The third week of the course focuses on helping students develop and maintain strong business relationships. The main emphasis of this week is on developing soft skills that are necessary to build relationships, earn trust, manage changes, establish a brand, and build a good reputation. Finally, in week 4, students receive different recommendations and techniques on how to design a plan to improve their soft skills and grow as a leader. Module one starts by answering a couple of fundamental questions: What is a cloud consultant, and what do they do? You explore the basic functions of this role to help you decide if being a cloud consultant is a job you’d like to pursue. In addition, you learn about critical thinking and analytical skills, which are important to the business world and for cloud consultants. You explore what they are, how to develop them, and some strategies that you can employ on your next business project. 8 videos6 readings1 assignment2 discussion prompts2 plugins In module two, you take on the role of a cloud consultant who is working with a customer. You start the module by walking through a common project for a cloud consultant: migrating a workload from an on-premises data center to AWS. During this process, you learn about the types of meetings that you might experience, and the different types of job functions that you might perform in the organization. By the end of the module, you should have a solid understanding of the different tasks and activities that a cloud consultant might do in their workday. 9 videos3 readings2 assignments Module three focuses on building and maintaining business relationships. In business, who you know can be as important as what you know. In this module, you focus on building and maintaining a network of professional connections. In addition to networking, it’s important for you to develop your own professional brand. To that end, you also explore how you can establish your brand and maintain a positive image in the business world. 5 videos2 readings2 assignments In module four, you explore how you can continuously improve your skill set. Because business is always changing, you should also consider how you can keep evolving your skills. You learn how to create a plan to develop your skills and work on addressing your weaknesses. As you develop new skills, it’s important to manage your time and make the most out of what you have. At the end of the module, you learn the principles behind designing effective resumes, and then you go hands-on to review and update your own resume. 5 videos4 readings3 assignments1 plugin

4 modules

Beginner level

10 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/aws-cloud-consultant-skills

Digital Forensics Concepts

12,763

4.7

Denise Duffy

Infosec

[]

In the Digital Forensics Concepts course, you will learn about legal considerations applicable to computer forensics and how to identify, collect and preserve digital evidence. This course dives into the scientific principles relating to digital forensics and gives you a close look at on-scene triaging, keyword lists, grep, file hashing, report writing and the profession of digital forensic examination. This introductory course provides a broad overview of computer forensics as an occupation by exploring methodologies used surrounding digital forensics. In addition, the student acquires open-source forensic tools to use throughout this path. 4 videos3 readings In this module, you'll explore the laws that apply to digital forensics. Multiple state and federal laws apply to the field of digital forensics, as well as ethical concerns. This module demonstrates information commonly needed in a search warrant and a preservation request. The scope of search authority is covered, as well as the limitations of a consent search and guidelines surrounding wiretaps. 3 videos An introduction to the scientific principles of digital forensics. This module covers scientific principles that apply to digital forensics. The student learns about transfer of evidence, the difference between a witness and an expert witness and "big data" concerns and solutions. 2 videos Prepare for the practical side of forensic examinations with this module on physical evidence handling. In addition to forensic examinations, most digital investigators must understand how to manage physical evidence before, during and after leaving the scene. This module explores what to bring to a scene and how to prepare and label digital evidence for documentation purposes. You'll also examine how to collect and preserve the evidence for transportation and secure storage. 5 videos Explore the details of digital device triage. Triaging a digital device is essential knowledge. Proper on-scene triage prevents the loss of volatile data and the collection of unnecessary devices. This module discusses capturing RAM, recognizing and dealing with encryption and destructive processes and triaging devices with a forensic boot media. 3 videos A look at hash values and hash algorithms. In this module, the student learns how to use hash values as a way to include or exclude files from an investigation. This includes a discussion of different types of hash algorithms and how to hash individual files versus hashing drives. 3 videos In this module, you'll explore the importance of creating a disk image. Forensic examiners need to be meticulous in their work to avoid cross-contamination when creating a bit-stream copy. This module explains the importance of sterilizing media, how to validate tools, proper application of the write-blocker and validating the forensic bit-stream copy. 5 videos Explore the details of keyword and grep searches. How to conduct a keyword search using automated tools and how to establish a keyword list is covered in this module. The student receives an overview of grep, as well as completing a grep search using an automated tool. 4 videos A look at network basics for the computer forensics investigator. This module describes what a network is, how it functions, what IP addresses are and an IP address’s function on the network. This module also explores what a MAC address is and why it is vital to network forensics. Internet protocols are also covered. 4 videos A look at the importance of reporting and peer review. Report writing and peer review are of utmost importance. In this module, the student examiner learns what information to include and what does not belong in a final report. The student views several example reports, as well as generates a report using forensic software. 3 videos1 assignment 2 videos2 readings

11 modules

Intermediate level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/digital-forensics-concepts

Foundations of Healthcare Systems Engineering

12,801

4.7

Dr. Matthew (Matt) Montoya

Johns Hopkins University

[]

Through dynamic video lectures and practical application questions, you will learn about the Foundations of Healthcare Systems Engineering. In this course you will learn about the current lack of synchronized, efficient, and integrated healthcare systems, which are some of the drivers for improvements to healthcare delivery. Also in this course, you will learn about the different types of systems and how they are translated to the healthcare field for appropriate systems engineering process applications, with exemplars. Upon system type articulation and mapping, the systems engineering approach will be introduced to help begin the process of: 1) investigating healthcare challenges, needs, and requirements development; 2) developing system concepts, that are derived from requirements, and then realized in physical and process form; and finally, 3) the establishment of means to verify, validate, and deploy healthcare systems that address the need and meet requirements. Applications and exemplars will be provided. In this module, you will be introduced to the drivers and needs to improve healthcare and how systems engineering can enable this betterment. 6 videos1 assignment2 plugins This module will introduce you to the different system types, their characteristics, attributes, with exemplars. 4 videos1 assignment In this module, the systems engineering approach will be introduced to enable you to conceptualize the application for healthcare system challenge resolution. 7 videos1 assignment This module will introduce you to the variety of healthcare systems and then map these systems to the appropriate system type for systems engineering application within the systems engineering approach. 8 videos1 reading1 assignment1 plugin

4 modules

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/foundations-of-healthcare-systems-engineering

Nuts and Bolts of U.S. Immigration Law

8,613

4.9

Fernando Chang-Muy

University of Pennsylvania

[]

This course begins by exploring short term entry and long term entry into the United States. We will cover the various means of short term entry and long term entry, as well as the general application processes. We will also examine exclusion and deportation in the United States. In particular, we will discuss how and why individuals may not be admitted into the United States and possible reasons for deportation or removal. Lastly, we will cover the process of how to become a United States citizen and the various requirements for naturalization. Welcome to this course on U.S. Immigration Law! In this introductory module, we will discuss short term entry in the United States. This will include a discussion about the various means of short term entry and the general application process. We will also cover the fundamentals of student visas, work visas, and humanitarian visas. 7 videos4 readings1 assignment1 discussion prompt This module explores entering the United States as a lawful permanent resident. We will start by discussing the difference between short term entry and long term entry. Then, we will discuss the various ways to obtain lawful permanent resident status. This includes family petitions, self petitions, employer based petitions, asylum petitions, special immigrant juvenile status, and the diversity visa program. 7 videos7 readings1 assignment This module covers exclusion and deportation in the United States. First, we will explore how and why individuals may be excluded or not admitted into the United States. Then, we will discuss possible reasons for deportation or removal. 8 videos4 readings1 assignment In this module, we will discuss how to become a United States citizen. We will start by discussing how to gain U.S. citizenship. We will then cover the various requirements for naturalization. Finally, we will explore the naturalization process. 6 videos2 readings1 assignment

4 modules

Intermediate level

10 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/us-immigration-law

TensorFlow on Google Cloud

49,044

4.4

Google Cloud Training

Google Cloud

['Tensorflow', 'Python Programming', 'Machine Learning', 'keras', 'Build Input Data Pipeline']

This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use. This module provides an overview of the course and its objectives. 1 video This module introduces the TensorFlow framework and previews its main components as well as the overall API hierarchy. 4 videos1 reading1 assignment Data is the a crucial component of a machine learning model. Collecting the right data is not enough. You also need to make sure you put the right processes in place to clean, analyze and transform the data, as needed, so that the model can take the most signal of it as possible. In this module we discuss training on large datasets with tf.data, working with in-memory files, and how to get the data ready for training. Then we discuss embeddings, and end with an overview of scaling data with tf.keras preprocessing layers. 10 videos1 reading1 assignment2 app items In this module, we discuss activation functions and how they are needed to allow deep neural networks to capture nonlinearities of the data. We then provide an overview of Deep Neural Networks using the Keras Sequential and Functional APIs. Next we describe model subclassing, which offers greater flexibility in model building. The module ends with a lesson on regularization. 10 videos1 reading1 assignment2 app items In this module, we describe how to train TensorFlow models at scale using Vertex AI. 3 videos1 reading1 assignment1 app item This module is a summary of the Build, Train, and Deploy ML Models with Keras on Google Cloud course. 4 readings

6 modules

Intermediate level

https://www.coursera.org/learn/intro-tensorflow

89%

Flight mechanics - The basis

18,463

4.7

Eric Poquillon

ISAE-SUPAERO

[]

More than one century after the Wright brothers' first flight, the flight still defy our intuition. You will learn here how to name the different parts of the airplane and how to describe and quantify its geometry. For that, we need now to share a precise vocabulary to describe the airplane's movement and attitude in space, and a refresher on basic general mechanic principles. You will remind how Newton's 2nd law allows you to determine what force must be applied on an apple - or on an airplane, to modify the magnitude and direction of its speed. Coming back on the concepts of kinetic energy and potential energy, you will discover the very useful concept of total height and you will be able to explain how an airplane can quickly exchange speed for altitude, while changes in total height are much slower. In the end, you will discover that only a very small number of forces apply on an airplane in flight and that you will be able to classify those that change its energy state and those that modify its trajectory. You will discover the concept of load factor and understand why the pilot of a combat aircraft can feel a weight nine-time greater than his actual weight! Finally, we will establish the lift and propulsion equations, that form the basis of flight mechanics, and you will be able to compute the lift and thrust necessary to follow a given trajectory at a given speed. This course is for anybody interested in learning more about how planes work, the physics of flying, or flight mechanics. It will be of particular interest to undergraduate students in aerospace engineering, trainees as well as senior pilots, journalists, and professionals in the aeronautics sector. Although some mathematical formalism may be present sometimes. It is always doubled by sketches, figures, and hands-explanations. So that, anybody can skip the formulas without losing the core understanding of the concepts. No apples were harmed in the making of this course... This course is only a foretaste of the mechanics of flight. ISAE-SUPAERO and Eric Poquillon will offer you other courses and the first specialization in autumn 2021. Initially, three courses will be published to answer several questions: Can we fly as high as we want? What is a stall? Why do some planes have propellers and others have jet engines? Is an airplane always stable? How do you control an airplane following an engine failure? All this and more will be covered in this series of flight mechanics courses. This course is a part of the specialization "Fundamentals of Flight mechanics". Along this first week, we want you to get acquainted to the airplane. We will first learn how to name the different parts of the airplane and how to describe and quantify its geometry. And we will see through an exercise that concepts that seem well defined, like the surface of the wing (wing surface), can be, in practice, difficult to measure. This part will allow us to share a common and precise vocabulary. 3 videos4 readings3 assignments2 discussion prompts1 plugin We need now to share a precise vocabulary to describe the airplane's movement and attitude in space, and a refresher on basic general mechanics principles. You will review how Newton's second law allows you to determine what force must be applied on an apple - or on an airplane, to modify the magnitude and direction of its speed. Coming back on the concepts of kinetic energy and potential energy, you will discover the very useful concept of total height and you will be able to explain how an airplane can quickly exchange speed for altitude, while changes in total height are much slower. To conclude this week, we invite you on a tour of our full flight simulator Pegasus (Pegase in French), to see how clever use of those concepts in a Head-Up Display might allow you to conduct a perfect approach and landing without a single glance at your speed or altitude indicators. 3 videos4 readings4 assignments1 discussion prompt It's time to apply your knowledge to the airplane! You will discover that only a very small number of forces apply on an airplane in flight and that you are able to classify those that change its energy state and those that modify its trajectory. You will discover the concept of load factor and understand why the pilot of a combat aircraft can feel a weight nine-time greater than his actual weight! You will come on board our DR400 light airplane (not a combat airplane indeed) with Newton's apple to better understand what this load factor actually means. Finally, you will establish the lift and propulsion equations, that form the basis of flight mechanics, and you will be able to compute the lift and thrust necessary to follow a given trajectory at a given speed. No apples were harmed in the making of this course. 5 videos1 reading3 assignments In this final graded assessment, you will check your knowledge and apply it to solve an actual flight dynamic problem : how to fly a loop in a glider. 2 readings5 assignments

4 modules

Beginner level

https://www.coursera.org/learn/basis-flight-mechanics

89%

Business English: Basics

137,761

4.5

Kin Tang

The Hong Kong University of Science and Technology

['Grammar', 'Business Communication', 'Communication', 'Writing']

This course aims to improve your Business English language skills by developing your vocabulary and reading skills and your understanding of tone, style and knowledge of communication methods. We'll also cover how these language skills can enhance audience analysis, business case analysis and basic business communication strategies. Skills learned in this course will often be referred to and needed to complete the speaking, writing and cross-cultural communications courses of this Specialization. After completing this course, you will be able to: - describe things and events in the context of Business English - make requests in the context of Business English - support arguments in the context of Business English - use appropriate tone and style according to the context of Business English - conduct an audience analysis - match audience with the purpose and medium of communication - analyse and summarise business data Welcome to Week 1! This week, we will cover Module 1 where we introduce you to the objectives and structure of this Specialization and course. 3 videos4 readings3 discussion prompts Welcome to Week 2! This week we will cover Module 2 where we introduce you to basic communication and language skills you will use in general business situations. You will also be introduced to vocabulary and language skills common to business communications. 7 videos7 readings3 assignments1 peer review1 discussion prompt Welcome to Week 3! This week we will cover Module 3 where we will introduce you to common styles of English you will use for different spoken and written situations in general business situations. You will also be introduced to vocabulary and language skills common to business communications. 7 videos6 readings3 assignments2 peer reviews1 discussion prompt Welcome to Week 4! This week we will cover Module 4 where we will introduce you to ways of identifying the purpose and audience for spoken and written documents in general business situations and how this can affect language use. You will also be introduced to vocabulary and language skills common to business communications. 7 videos5 readings3 assignments1 peer review1 discussion prompt Welcome to Week 5! This week we will cover Module 5 where we will introduce you to ways of analyzing business cases and strategies for critical reading. You will also be introduced to vocabulary and language skills common to business communications. 5 videos8 readings3 assignments1 peer review1 discussion prompt Welcome to Week 6! This week we will cover Module 6 where we will conclude the course and you will need to complete the final exam and post-course survey. 1 reading1 assignment

6 modules

20 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/business-english

97%

Generative AI for Data Science

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Applying Generative AI in data projects', 'Anomaly detection with GenAI', 'Analyzing GenAI data security and privacy', 'Data augmentation with GenAI', 'Integrating GenAI into data workflows']

Did you know Generative AI can enhance data accuracy and operational efficiency in data science? This Short Course was created to help data scientists and AI enthusiasts unlock the full potential of Generative AI in their data-driven projects. Within this 3-hour-long commitment, you will learn how to explore and leverage GenAI applications, identify key use cases like data augmentation and anomaly detection, and analyze crucial data security and privacy issues. By completing this course, you'll be able to apply advanced AI techniques to real-world data challenges, ensuring your projects are both innovative and ethically sound. Blending cutting-edge AI technology with practical, industry-specific applications makes this course unique. To be successful in this project, you will need a solid foundation in Python, basic machine learning principles and an understanding of fundamental data science concepts. Upon completing this course, you will be proficient in harnessing the transformative capabilities of generative AI (GenAI) within the data science landscape, specifically in marketing and advertising. Additionally, you will explore the ethical and operational implications of GenAI in data science. By the end of the course, you will be equipped to integrate the innovative potentials of GenAI technologies into your practices, effectively balancing innovation with integrity. 1 video1 reading By the end of this lesson, you will understand how Generative AI is transforming Data Science. We'll explore how these models identify data patterns to create original content, improve fluorescence microscopy by reducing cell damage, enhance anomaly detection in datasets, and revolutionize SMS marketing to keep brand consistency. This lesson will show the wide applications and benefits of Generative AI in various data science challenges. 5 videos1 assignment By the end of this lesson, you will learn about the applications and benefits of Generative AI in data science, especially for optimizing local LLM (Large Language Model) deployments. We'll cover the advantages of running models locally, such as faster iteration speeds, and the computational demands of large models. You'll also learn about quantization techniques to enhance training and reduce memory usage, as well as the LoRA technique for fine-tuning. Finally, you'll see a practical demo of fine-tuning an open-source model using both LoRA and quantization, giving you practical skills to improve AI model efficiency locally. 5 videos1 assignment By the end of this lesson, you will learn how generative AI improves feature engineering in SMS campaign data. This AI automates the extraction of complex patterns and relationships, making it more efficient and powerful than traditional manual methods. We'll also discuss how previous techniques required extensive domain expertise and often lacked scalability and adaptability. Additionally, you'll get a tutorial on using a generative AI model to automatically label different parts of SMS campaign messages with a step-by-step code walkthrough in Python. This approach will show you how generative AI transforms raw data into actionable insights for better campaign management. 3 videos4 readings1 assignment By the end of this lesson, you will be able to analyze the security and privacy impacts of Generative AI in data science. We'll explore ethical issues like data privacy, consent, and bias, and discuss how to develop and deploy AI responsibly. You'll learn about creating synthetic data using methods like differential privacy and data anonymization to ensure ethical compliance. This lesson aims to help you make responsible decisions and think critically about ethical issues in AI applications, preparing you to handle complex challenges in data science. 4 videos1 reading2 assignments

5 modules

Intermediate level

3 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/generative-ai-for-data-science

Global Sodium Reduction Strategies

Enrollment number not found

Rating not found

Megan E. Henry, PhD

Johns Hopkins University

[]

This course will help guide policy makers, advocates, and program managers as they design, plan, and implement sodium reduction interventions to protect public health. We invite you to see what interventions have been proven at scale, what shows promise, and what lessons have been learned along the way from the implementation of sodium reduction strategies all around the globe. Our emphasis is implementation in settings with resource constraints. There are nine modules in this course. The first two modules set the stage with information on the science of sodium and context for lowering intake at a population level; the next five modules describe specific interventions; and the final two modules discuss comprehensive strategies in the wider context of public health, as well as tools for monitoring and evaluating interventions. Global Sodium Reduction Strategies was created by a team at the Johns Hopkins Bloomberg School of Public Health and is supported by the Resolve to Save Lives Initiative. In this first module we provide a course overview. We will explain the significant role that sodium plays in the development of high blood pressure and cardiovascular disease in people all over the world. Sodium intake needs to be lowered in every country to benefit the health and economic well-being of all populations. But how do we do it? What has worked before? We will discuss these topics throughout the course. First, let’s take a look at cardiovascular disease around the globe. Then we’ll look at what sodium does in the human body, what happens over time when we eat too much sodium for our bodies’ needs—and what can happen when we lower the amount of sodium we eat. 9 readings1 assignment9 plugins It is important to understand the setting before we take a look at the different sodium reduction intervention options that could work there. Every country will require more than one approach, but combining interventions will be most effective when sources of sodium are understood. Before you select the best interventions for your country, you need to understand how people consume the majority of their sodium. 3 readings1 assignment5 plugins With sodium intake so high in many countries, many individuals consume more sodium than is safe. This includes individuals who are currently in good health but will likely develop high blood pressure over time, individuals with known high blood pressure, and individuals who have undiagnosed high blood pressure. The entire population will benefit from the protection that mandatory sodium limits provide, especially when it is part of a multi-component strategy to reduce sodium in the food supply and protect public health. 5 readings1 assignment5 plugins This module will walk you through the basics of front-of-package labels (FoPL), such as what the intervention is supposed to do, and who it is supposed to reach. It turns out that even children take part in food purchasing when labels are accessible to all and easy to understand! A strategy to use FoPL will require a setting where packaged foods are common. But as we’ll explore later in the module, this is now practically everywhere around the globe. FoPL are more easily interpreted when they convey a recommendation rather than simply stating levels of nutrients. In some regions, the existing legal structure is already sufficient to begin drafting and implementing regulations. In other regions, laws must be passed first. We will share lessons learned from real people who have worked on instituting FoPL in different countries. You will learn how these previous efforts formed our current understanding of best practices, and the importance of focusing on consumer understanding rather than industry-led goals when it comes to label design. We will provide basic guidelines for implementation. We will end with a real-world example from Chile, where challenges were addressed and FoP warning labels were successfully implemented. 6 readings1 assignment6 plugins In Module 5, we will describe the rationale for using low-sodium salts as a potential strategy to reduce dietary sodium intake at the population level. You will learn what low-sodium salts are, their health benefits, and the potential risks associated with their use. We will discuss what to consider before promoting the use of low-sodium salts at the population level. Low-sodium salts are available for sale in a wide range of real-world settings, but their implementation on a large scale has not yet been reported. We will conclude by describing how low-sodium salts were used as a public health strategy to lower sodium intake in two different populations. 6 readings1 assignment5 plugins In this module we will explore public food procurement policies. Governments already have requirements in place for how food is purchased, so why not optimize them to serve healthier food? It’s not only the amount of salt that can be lowered, but other important aspects of a healthy diet that can be incorporated as well, such as increased servings of fruits and vegetables, fewer processed foods, and reduced sugar and unhealthy fats. Food procurement policies can improve the local food environment by increasing the availability of healthier products, and they can also promote the purchase of local agriculture products, which strengthens local food systems and economies, and reduces the impact on our climate. We will discuss the strategies for developing and implementing strong and impactful public food procurement policies, as well as how to assess for compliance and evaluate these policies. 6 readings1 assignment7 plugins The focus of this module is on food consumed outside the home from independent restaurants, chain restaurants, and street vendors. Around the world, there is a high consumption of food prepared outside the home. In many countries, it’s a growing source of food and sodium intake. Food prepared outside the home is often more sodium dense than home-prepared food. As a result, interventions in the restaurant environment are crucial for addressing population sodium intake. While there are restaurant interventions in place globally, there are not specific nutrient limits for restaurant chain meals, nor global standards for restaurant portions or serving sizes. Further, the policies that have been developed so far have either had limited evaluation, or have shown inconclusive results. While there is still much to learn about this complex environment, countries and cities around the world are providing potential solutions that offer hope for improving the food environment and creating healthier diets. 7 readings1 assignment7 plugins In this module, we will discuss how the most successful and/or innovative approaches to sodium reduction can be combined and placed within a wider context of public health interventions. Multi-component, population-level policy changes are the most effective. We will explore here what has worked. 7 readings1 assignment7 plugins This module provides guidance regarding the tools available to assist governments in assessing progress and achieving goals once programs are implemented. Planning for regular surveillance is essential to ensure that sodium reduction strategies meet specific targets on time. Equally important is allowing for a system that can identify and address challenges, so improvements can be made to existing and future programs. Finally, we will explain the importance and methods of recording and reporting progress. 8 readings1 assignment8 plugins

9 modules

Beginner level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/sodium

Generative AI: Elevate your Data Engineering Career

2,502

4.9

Rav Ahuja

IBM

['Convolutional Neural Network', 'Information Engineering', 'Querying Databases', 'Data Generation', 'Generative AI']

Data engineering processes have undergone an amazing transformation since the advent of Generative AI. In this course, you will explore the impact of generative AI on data engineering. You as a data engineer can use Generative AI to enhance productivity by introducing innovative ways to deliver projects. Data engineering is responsible for building strong data pipelines, managing data infrastructure, and ensuring high-quality data evaluation. This course is suitable for existing and aspiring data engineers, data warehousing specialists, and other data professionals such as data analysts, data scientists and BI analysts. You will learn how to use and apply generative models for tasks such as architecture design, database querying, data warehouse schema design, data augmentation, data pipelines, ETL workflows, data analysis and mining, data lakehouse, and data repositories. You will also explore challenges and ethical considerations associated with using Generative AI. Demonstrate your new generative AI skills in a hands-on data engineering project that you can apply in your real-life profession. Then, complete your final quiz to earn your certificate. You can share both your project and certificate with your current or prospective employers. In this module, you will acquire the necessary skills to use generative AI tools for data engineering effectively. You will learn some successful implementations of generative AI tools in databases, data warehousing schema design, data generation, augmentation, and anonymization. You will also learn how to use generative AI for infrastructure design. 9 videos2 readings3 assignments5 app items1 discussion prompt7 plugins This module will give you the skills and knowledge to effectively use generative AI to prepare data pipelines and ETL workflows. In addition, you will acquire skills in querying databases, data analysis, and data mining. You will also understand the importance of ethical practices in using generative models. 8 videos1 reading3 assignments6 app items3 plugins In this module you will work on a real-world dataset and apply the skills acquired in this course to the test. You will use Generative AI to perform multiple Data Engineering operations in terms of planning, preparing and processing the data. 1 video2 readings1 assignment2 app items1 plugin

3 modules

Intermediate level

12 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/generative-ai-elevate-your-data-engineering-career

Musician’s Professional Toolbox: Your Portfolio Career Specialization

Enrollment number not found

4.9

Jeffrey Nytch

University of Colorado Boulder

['Task Management', 'Resume writing', 'Networking', 'Marketing', 'Branding', 'Task Management', 'Resume writing', 'Networking', 'Marketing', 'Branding']

Are you a musician with big dreams and a passion for creating music? Are you ready to take your musical career to the next level? If so, the “Musician’s Professional Toolbox” may be just what you need! In this specialization you will learn career development skills and tools for freelance musicians. Gain critical skills in self-assessment, branding, marketing, promotion, gigging, and teaching studio setup. Define your artistic vision, set meaningful goals, and expand your professional network. From personal and artistic development to branding, promotion, and strategic career management, you'll come away from this sequence of courses equipped with the tools to successfully navigate the music industry. Applied Learning Project Learners will produce professional materials to help launch and support careers as musicians, including cover letters, resumes, and headshots. Additional assignments allow learners to prepare to network successfully, build and maintain clientele, develop a personal brand and mission statement, and more. Understand your unique mix of musical and non-musical skills and how those skills can inform your career development. Develop better habits: Link task management to near-term, mid-term, and long-term goals. Identify ways to measure outcomes and gauge success. Begin building/expanding a professional network. Identify the character of visual and audio materials that best capture the professional image you wish to project. Use a variety of demographic and psychographic parameters to define your customer market and/or audience. Identify marketing channels and how they are used to promote your brand and build your business. Employ strategies for effective social media content. Learn the three types of resumes (performance resume, general music resume, and skills resume), when to use them, and how to format them. Apply basic concepts of composition, lighting, and audio quality to create compelling promotional images and demo videos. Write a selection of prose biographies for a variety of settings that illustrate your artist’s Mission Statement. Identify the key components and visual “feel” of a professional website. Articulate your Unique Selling Proposition. Use the Business Model Canvas to determine the core functions required to effectively manage your portfolio career. Complete a comprehensive growth and recruitment plan for your teaching studio and identify the competitive landscape. Seek out and book performance opportunities in a variety of settings.

4 course series

Intermediate level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/music-career-toolbox-managing-your-portfolio-career

Researcher's guide to RNA sequencing data

Enrollment number not found

Rating not found

Candace Savonen, MS

Fred Hutchinson Cancer Center

['Gene Expression', 'RNA-seq']

This course is a follow up course to "Choosing genomics tools" which dives into further detail about RNA informatics methods! This course is for individuals who: - Have taken Researcher's Guide to Fundamentals of Omic Data - Have RNA data and don’t know what to do with it. - Want a basic overview of their RNA focused data type. - Want to find resources for processing and interpreting RNA data What this course will cover: - Fundamentals of RNA methods. - Resources you may consider looking into for your own purposes. - Questions you should ask yourself and your colleagues about your goals and experimental design. What this course will NOT cover: - Code needed to process your data. - Details about every type of experimental design. - Everything you’d need to know to make you a computational biologist. In other words we still highly encourage you to consult your informatics and computational colleagues, especially those who may have done any handling of data you are trying to learn about. In this first module we introduce the goals of this course an do an overview of the available methods for RNA methods, otherwise known as gene expression. 3 videos1 reading2 assignments1 discussion prompt In this module we dive into Bulk RNA-seq methods for evaluating gene expression of tissue. 1 video2 readings2 assignments1 discussion prompt In this module we dive into single cell RNA-seq methods for evaluating gene expression of single cells. 1 video2 readings2 assignments1 discussion prompt In this module we dive into gene expression of tissue but with spatial information. 1 video2 readings2 assignments1 discussion prompt To wrap up this course, we have a quick section about gene expression microarrays before we wrap up the course with a final course knowledge check. 3 readings1 assignment1 discussion prompt

5 modules

Intermediate level

4 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/researchers-guide-to-rna-sequencing-data

Getting Started with Automation 360

4,186

4.5

Automation Anywhere, Inc.

Automation Anywhere

['Writing inline scripts within RPa bots', 'Deploying Bots to automate business processes', 'Creating Attended and Unattended RPA bots using AARI']

Automation 360(tm) is the leading cloud-native end-to-end intelligent automation platform used by the world's top enterprises to automate business processes across systems and applications. This course is designed to introduce Robotic Process Automation (RPA), how RPA can be used to identify business processes for automation, and how to use Automation Anywhere Robotic Interface (AARI) to automate back office and front office business processes. Experienced and novice RPA developers will learn how to build simple to complex RPA bots using Automation 360 action packages to automate repetitive and mundane work processes to reduce human errors and improve business outcomes. In this module, you will learn about the scope and benefits of Robotic Process Automation (RPA). 5 videos In this module, you will learn about Robotic Process Automation (RPA). 8 videos In this module, you will learn how to identify business processes for automation and the various tools available for feasibility and complexity analysis of processes. You will also learn how Discovery Bot helps in documenting and automating identified business processes. Learning will be reinforced through demonstrations. 9 videos In this module, you will learn to build a software bot using Automation 360. This course will help you use various Automation 360 actions to build task bots intuitively to meet your business process automation objectives. The learning will be reinforced through a business use case and step by step demonstration. 10 videos In this module, you will learn how to build resilient bots using Automation Anywhere Automation 360. This course describes the need for building resiliency within bots and covers the basic governing principles for building resilient bots. The learning will be reinforced through different business use cases and step-by-step demonstrations. 6 videos In this module, you will learn how to build a bot for scalability. This course describes how to build a bot with a reusable code base that can be deployed across multiple business functions. The learning will be reinforced through different business use cases and step-by-step demonstrations. 4 videos In this module, you will learn the benefit of using 'RPA bots for Excel' and how it simplifies the process of executing excel-related tasks without accessing the Automation 360. 10 videos In this course, you will learn about the packages and actions available in Automation 360 that you can use to invoke inline scripts. You will also learn about how to use Python, JavaScript, and VBScript code snippets in Automation 360. 6 videos In this module, you will learn how Automation Anywhere Robotic Interface (AARI) can be used to automate back and front office tasks seamlessly. You will also learn how organizations will benefit as a result of such automation. 15 videos 2 assignments

10 modules

Intermediate level

4 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/automation-360

Health Information Technology Fundamentals

16,143

4.8

Ashwini S. Davison, M.D.

Johns Hopkins University

[]

In this course you will receive an overview of the health IT ecosystem with a specific focus on the role of electronic health records (EHRs). You’ll be introduced to the factors that contributed to the move from paper records to digitized records and who the most common vendors are. We’ll go over features of EHRs such as computerized provider order entry, clinical decision support, documentation capabilities, and medication reconciliation. Like a physician’s stethoscope, the EHR has become an important tool in healthcare delivery and plays a part throughout the patient’s journey. You’ll go through each of the steps from patient scheduling, to front desk registration, outpatient visits, emergency room encounters, and inpatient admissions. During the course, we’ll also cover examples of how technical issues related to the EHR can be as simple as problems with logging or password resets. But how they can also be more complex related to alerts that are firing and the display of information. Although some of those challenges are beyond the scope of the IT support staff, having familiarity with the scope of potential problems and the broader EHR landscape is important. This course also includes an introduction to database architecture, servers, and interfaces. We wrap up by discussing the importance of training end-users on healthcare technology and the way in which effective change management strategies are crucial. In this module, you’ll be introduced to electronic health records (EHRs) and why they’re important from a patient care perspective. We will review the benefits of electronic health records and become familiar with what the most common EHR companies are that you should be familiar with. You’ll see the full lifecycle of the role an EHR plays starting from the point of scheduling and front desk registration. You’ll learn about the way ambulatory or outpatient encounters are handled. We’ll then discuss emergency room visits, inpatient admissions and the role of Health IT at the time of discharge from the hospital. We will highlight the integration of multiple steps in care delivery that revolve around this important tool. You’ll learn about the way patient data moves through the system, how clinicians might need technical assistance and what your role in troubleshooting or escalating issues could be. 4 videos2 readings1 assignment In this next module you’ll gain an even better understanding of how electronic medical records play an integral role in healthcare delivery. We’ll cover common EHR applications in Ambulatory, Inpatient, Emergency, Pharmacy, Radiology, and Operating Room (OR) settings. You’ll be introduced to some of the important patient information that’s documented in the EHR, such as allergies and medications. You’ll also get a behind the scenes view of what happens when an order placed by a provider needs to be modified. The importance of teamwork and communication in addressing issues is highlighted. 6 videos2 readings1 assignment This module covers clinical decision support (CDS) and how these tools are embedded into electronic health records (EHRs). We’ll go over common types of CDS such as alerts, preventive health reminders, configuration of order sets and calculators. When it comes to clinical decision support, there are CDS committees at a hospital or health system level that are responsible for reviewing the way CDS is functioning in practice. Physicians, nurses, pharmacists and analysts serve on these committees. Each organization has its own governance structure and meeting schedule for these kinds of groups. When there are issues that arise, these committees are decide how best to modify the CDS to ensure that the EHR is helping providers provide the best care. They also make decisions around what alerts should fire for providers, and what exclusions should be applied to limit alert fatigue. We’re providing you with this perspective so that you understand that not all issues related to the EHR can be addressed by the help desk, level 2, level 4 or even application specific teams. During this module, you’ll also be introduced to technical terminology related to databases, servers, and interfaces. 6 videos1 reading1 assignment Now that you’ve been oriented to electronic health records, clinical decision support, and databases, we’re going to cover the importance of and process of training end-users in healthcare. You’ll see a scenario where a health IT trainer teaches a clinical end-user about the process of logging in, getting authenticated, and looking up patients. You’ll want to be familiar with roles of super-user, application specialists, and system trainers. The EHR database structure is complex and there are many different environments that exist in order to ensure that users can be educated appropriately. Applications in health IT are frequently undergoing updates, so you’ll want to be familiar with the different training environments and how data can be migrated. We’ll also cover the change management process involving EHR upgrades and importance of effective communication, significant preparation, and downtime procedures. 4 videos2 assignments

4 modules

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/health-it-fundamentals

95%

Python Programming for Quantum Computing

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['Python Programming', 'Python OOP', 'Python Data Structures', 'Python Anaconda Installation', 'Python for Quantum Computing']

This course is designed to provide a solid foundation in Python programming, tailored for individuals interested in quantum computing. The first section begins with an introduction to Python from scratch, walking you through the installation of Anaconda on both Windows and macOS, followed by an overview of Python’s core concepts. You’ll learn to write your first code using numbers, variables, strings, and more advanced data types like lists, dictionaries, and tuples. By the end of this section, you'll have set up your environment and mastered key programming basics with practical hands-on coding in Jupyter notebooks. In the second section, the focus shifts to control flow and data manipulation. You’ll explore Boolean values, logical comparisons, and conditional if statements, essential for writing decision-based programs. This section also covers loops (for and while) and the crucial commands such as break, continue, and pass, enabling you to manage complex iteration scenarios. By diving into practical use cases, you’ll also enhance your ability to manipulate data structures like lists. Furthermore, this section includes introductions to Python methods, zip, and random functions—tools that will help streamline your coding experience. The final section delves into more advanced topics like functions and object-oriented programming (OOP). You’ll start with basic function definitions, input/output handling, and advance to the practical use of functions in more complex scenarios. The object-oriented section introduces you to classes, methods, inheritance, and error handling, all crucial for building scalable, efficient Python programs. You’ll also learn about working with external libraries and creating your own Python modules, preparing you for more advanced programming challenges in quantum computing and beyond. This course is perfect for beginners who want to learn Python programming with a focus on quantum computing. It is suitable for anyone with a basic understanding of computers and no prior programming experience. Those with an interest in Python for data science, machine learning, or quantum computing will benefit from this foundational course. In this module, we will focus on setting up your Python environment and building a strong foundation in core Python concepts. From installing Anaconda to writing your first Python code, you'll explore basic data types and structures, laying the groundwork for advanced programming in Python. 14 videos2 readings In this module, we will explore how Python handles control flow and data manipulation. You will learn to work with if statements, loops, and logical comparisons, along with practical tips for real-world usage. Additionally, you'll dive deeper into advanced list techniques and methods for handling different data types. 14 videos In this module, we will delve into Python’s functions and object-oriented programming (OOP) features. You will explore how to create and use functions, understand the scope, and handle errors efficiently. Furthermore, you will work with classes and inheritance, and learn to utilize libraries and write your own Python modules. 16 videos1 reading1 assignment

3 modules

Beginner level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/packt-python-programming-for-quantum-computing-9rifk

Concept Art for Video Games

9,804

4.6

Ricardo Guimaraes

Michigan State University

[]

In this course we will talk about Concept Art. As a final project we will create a fully finished environment concept, ready for presentation. Throughout the 4 week modules will dive deeply into composition and digital painting techniques to bring your art skills to the next level! So, let's get started! Welcome to the Concept Art Module! In this module you will learn how to create a fully finished Environment Concept Art for games. We will also cover best ways to study composition and digital painting techniques! 1 video In the first week of the Concept Art for Games Module, we will see the importance and advantages of making tiny studies from film frames. 3 videos1 peer review In the second week we will delve into the realm of 3D for Concept Art. 6 videos In the third week we will learn how to model the basic shapes of our scene and how to properly export the images to Photoshop 5 videos1 peer review In the fourth and last week we will learn how to paint over the 3D images to create a fully finished concept 8 videos1 peer review

5 modules

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/concept-art-video-games

AI and Climate Change

7,551

4.9

Robert Monarch

DeepLearning.AI

['Biodiversity Monitoring', 'Computer Vision', 'AI for Good project framework', 'Supervised Learning', 'Wind Power Generation Modeling']

In this course, you’ll start with a review of the mechanisms behind anthropogenic climate change and its impact on global temperatures and weather patterns. You will work through two case studies, one using time series analysis for wind power forecasting and another using computer vision for biodiversity monitoring. Both case studies are examples of where AI techniques can be part of the solution when it comes to the mitigation of and adaptation to climate change. 8 videos5 readings1 assignment1 ungraded lab 18 videos3 readings1 assignment3 ungraded labs 9 videos2 readings1 assignment1 ungraded lab 10 videos3 readings1 assignment3 ungraded labs

4 modules

Beginner level

14 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/ai-and-climate-change

Approximation Algorithms and Linear Programming

9,859

4.9

Sriram Sankaranarayanan

University of Colorado Boulder

['Travelling Salesman Problem (TSP)', 'Integer Programming', 'Approximation Algorithm', 'Linear Programming (LP)']

This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal solutions to problems arising from domains such as resource allocation, scheduling, task assignment, and variants of the traveling salesperson problem. Next, we will study algorithms for NP-hard problems whose solutions are guaranteed to be within some approximation factor of the best possible solutions. Such algorithms are often quite efficient and provide useful bounds on the optimal solutions. The learning will be supported by instructor provided notes, readings from textbooks and assignments. Assignments will include conceptual multiple-choice questions as well as problem solving assignments that will involve programming and testing algorithms. This course can be taken for academic credit as part of CU Boulder’s Masters of Science in Computer Science (MS-CS) degrees offered on the Coursera platform. This fully accredited graduate degree offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder This module introduces the basics of linear programs and shows how some algorithm problems (such as the network flow problem) can be posed as a linear program. We will provide hands-on tutorials on how to pose and solve a linear programming problem in Python. Finally, we will provide a brief overview of linear programming algorithms including the famous Simplex algorithm for solving linear programs. The problem set will guide you towards posing and solving some interesting problems such as a financial portfolio problem and the optimal transportation problem as linear programs. 7 videos2 readings5 quizzes1 programming assignment4 ungraded labs This module will cover integer linear programming and its use in solving NP-hard (combinatorial optimization) problems. We will cover some examples of what integer linear programming is by formulating problems such as Knapsack, Vertex Cover and Graph Coloring. Next, we will study the concept of integrality gap and look at the special case of integrality gap for vertex cover problems. We will conclude with a tutorial on formulating and solving integer linear programs using the python library Pulp. 6 videos4 quizzes1 assignment1 programming assignment4 ungraded labs We will introduce approximation algorithms for solving NP-hard problems. These algorithms are fast (often greedy algorithms) that may not produce an optimal solution but guarantees that its solution is not "too far away" from the best possible. We will present some of these algorithms starting from a basic introduction to the concepts involved followed by a series of approximation algorithms for scheduling problems, vertex cover problem and the maximum satisfiability problem. 5 videos4 quizzes1 programming assignment3 ungraded labs We will present the travelling salesperson problem (TSP): a very important and widely applicable combinatorial optimization problem, its NP-hardness and the hardness of approximating a general TSP with a constant factor. We present integer linear programming formulation and a simple yet elegant dynamic programming algorithm. We will present a 3/2 factor approximation algorithm by Christofides and discuss some heuristic approaches for solving TSPs. We will conclude by presenting approximation schemes for the knapsack problem. 11 videos5 quizzes1 programming assignment3 ungraded labs

4 modules

Advanced level

https://www.coursera.org/learn/linear-programming-and-approximation-algorithms

Cyber-Physical Systems: Modeling and Simulation

10,700

4.5

Ricardo Sanfelice

University of California, Santa Cruz

[]

Cyber-physical systems (CPS for short) combine digital and analog devices, interfaces, networks, computer systems, and the like, with the natural and man-made physical world. The inherent interconnected and heterogeneous combination of behaviors in these systems makes their analysis and design an exciting and challenging task. CPS: Modeling and Simulation provides you with an introduction to modeling and simulation of cyber-physical systems. The main focus is on models of physical process, finite state machines, computation, converters between physical and cyber variables, and digital networks. The instructor of this course is Ricardo Sanfelice (https://hybrid.soe.ucsc.edu), Associate Professor in the Department of Computer Engineering at the University of California Santa Cruz. 15 videos1 reading1 assignment1 peer review1 discussion prompt 12 videos1 assignment1 peer review 13 videos1 assignment1 peer review 11 videos1 assignment1 peer review

4 modules

Intermediate level

13 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/cyber-physical-systems-1

Entrepreneurship 4: Financing and Profitability

37,216

4.8

Kartik Hosanagar

University of Pennsylvania

['Venture Capital', 'Exit Strategy', 'Finance', 'Entrepreneurship']

Start-ups can benefit from a wide variety of financing options on the path to profitability, but how do you know which one to choose? This course explores different financing models, including bootstrapping, organic growth, debt and risk capital, and also provides a clear overview of equity financing including the key types of investors: angels, venture capital, and crowdfunding. You’ll learn about terms, and term sheets, exit modes and what exit strategy might be best for you. By the end of this course, you’ll have an understanding of what success looks like and how it can be financed. You’ll also be ready for the capstone project, in which you will get feedback on your own pitch deck, and may even be selected to pitch to investors from venture capital firms. This module was designed to introduce you to some of the key activities you can do in order to reach and sustain profitability. You'll learn the most important rule of entrepreneurship, the different kinds of business models, how to determine who your best customers are and how to develop strategies to retain them. You'll also hear from a successful entrepreneur and venture capitalist from Greylock Partners, who will talk about what indicators of success his firms looks for when deciding where to invest. By the end of this module, you'll be able to use business models to create customers who will come back for more, and know what key attributes to emphasize if you want to attract investment from venture capital. 4 videos1 reading1 assignment In this module, you'll learn the five most common methods of financing, and explore the financing process in depth. You'll also learn strategies for valuing your own company, and how venture capital and angel investors use valuations in negotiating milestones, influence and control. You'll discover how term sheets work, and what the terms mean, and you'll also examine the other terms used when financing with angel investors, friends and family, loans, and crowdfunding. By the end of this module, you'll be able to pick the financing pathway that's best for your enterprise, use common valuation strategies to set a reasonable price for your company, and negotiate favorable terms. 4 videos1 reading1 assignment This module was designed to give you a closer look at the advantages and disadvantages of both public and private financing, and to provide you with some simple but powerful tools for estimating how much capital you will need. You'll learn about the added benefits of working with venture capital firms, when and why to consider debt financing, and the latest trends in crowdfunding. You'll also learn to calculate how much money you are losing each month (the burn rate), and when you can expect to become self-sustaining (the breakeven point). By the end of this module, you'll be able to perform your own breakeven analysis so you can make a more informed choice about the best source of financing for you company. 5 videos1 reading1 assignment In this module, you'll learn the three key elements of your pitch to funders, and the examine the most common methods of exiting the entrepreneurial phase. You'll learn the structure and best practices for an executive summary, your pitch deck, and your pro-forma financial statements, and discover why these are so important to potential investors. You'll also learn the key differences between taking your company public and having it acquired by another, larger firm, and explore which method is best for preserving innovation. By the end of this module, you'll be able to create an effective pitch, and begin developing an exit strategy for your company that's relevant, effective and profitable. 4 videos1 reading1 assignment

4 modules

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/wharton-entrepreneurship-financing-profitabilty

95%

Content Development and Management

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Proofreading', 'content management', 'Content Creation', 'Content Management', 'Content Editing']

This course delves into the intricacies of Content Development and Management for Public Relations. You will learn about various PR content types and explore best practices for editing and proofreading to ensure message clarity and effectiveness. The course covers essential strategies for content management within PR, utilizing AI tools for content creation and automation to enhance efficiency and innovation. Additionally, you will develop a comprehensive content creation strategy, equipping you with the skills to craft impactful PR campaigns that align with organizational goals and engage target audiences effectively. By the end of this course, you will be able to: • Distinguish between different types of PR content based on their purpose and function within a PR campaign • Apply editing and proofreading best practices to ensure the quality and effectiveness of PR content. • Develop strategies for organizing and managing various types of PR content efficiently • Explain how AI tools can be used to enhance content creation and automate specific content management processes within PR • Create a content creation calendar that aligns with a PR strategy, effectively planning and scheduling content for optimal impact By the end of this course, you will be adept at developing and managing high-quality PR content, using AI tools to streamline processes, and planning content that aligns with strategic PR goals This module provides an introduction to the fundamentals of PR content, covering a variety of content types. You'll explore different forms of written content, examine visual and multimedia elements, and analyze social media content alongside best practices for each. 27 videos6 readings7 assignments In this module, you will explore the essentials of editing and proofreading, highlighting best practices to enhance PR content's clarity, consistency, and overall quality. You will learn to navigate and correct common PR mistakes, apply advanced proofreading techniques using tools like Microsoft Word, and adapt these skills across various PR formats, from press releases to PR campaigns. 19 videos7 readings9 assignments This module delves into the integral role of Content Management Systems (CMS) in Public Relations, offering insights into effective strategies for organizing, categorizing, and managing PR content using advanced CMS tools. It also focuses on optimizing workflow processes, fostering team collaboration within a CMS environment, and covers critical practices for archiving and retrieving PR content to ensure compliance and long-term accessibility. 21 videos7 readings7 assignments This module examines the integration of AI in Public Relations, starting with the basics of AI and its application in content creation and automation. You will explore how AI can drive written and visual content development, optimize content management, and enhance audience engagement through advanced AI tools. The module also addresses the ethical considerations of using AI, such as bias and transparency, while exploring emerging technologies and future trends that could shape AI's role in PR. 23 videos7 readings8 assignments This module delves into the strategic creation and use of content calendars in Public Relations, starting with the basics of constructing content calendars aligned with PR objectives. It explores tailoring content to meet strategic PR goals through effective audience segmentation and consistent messaging. Lastly, the module examines optimizing content timing and scheduling for maximum impact using audience behavior insights and analytics. 17 videos4 readings7 assignments In the final module, you will apply the concepts, strategies, and skills you have learned by developing a comprehensive PR campaign. 2 videos1 reading1 peer review

6 modules

Beginner level

32 hours to complete (3 weeks at 10 hours a week)

https://www.coursera.org/learn/pr-content-development-and-management

Data Visualization and Transformation with R

Enrollment number not found

Rating not found

Mine Çetinkaya-Rundel

Duke University

['Statistical Programming', 'Data Visualization', 'R Programming', 'Exploratory Data Analysis', 'Data Transformation']

This course is an introduction to data science and statistical thinking. Learners will gain experience with exploring, visualizing, and analyzing data to understand natural phenomena and investigate patterns, model outcomes, and do so in a reproducible and shareable manner. Topics covered include data visualization and transformation for exploratory data analysis. Learners will be introduced to problems and case studies inspired by and based on real-world questions and data via lecture and live coding videos as well as interactive programming exercises. The course will focus on the R statistical computing language with a focus on packages from the Tidyverse, the RStudio integrated development environment, Quarto for reproducible reporting, and Git and GitHub for version control. The skills learners will gain in this course will prepare them for careers in a variety of fields, including data scientist, data analyst, quantitative analyst, statistician, and much more. Hello World! In the first module, you will learn about what data science is and how data science techniques are used to make meaning from data and inform data-driven decisions. There is also discussion around the importance of reproducibility in science and the techniques used to achieve this. Next, you will learn the technology languages of R, RStudio, Quarto, and GitHub, as well as their role in data science and reproducibility. 4 videos10 readings1 assignment2 discussion prompts1 plugin In our second module, we'll advance our understanding of R to set the stage for creating data visualizations using tidyverse’s data visualization package: ggplot2. We'll learn all about different data types and the appropriate data visualization techniques that can be used to plot these data. The majority of this module is to help best understand ggplot2 syntax and how it relates to the Grammar of Graphics. By the end of this module, you will have started building up the foundation of your statistical tool-kit needed to create basic data visualizations in R. 4 videos5 readings1 assignment1 discussion prompt1 plugin In this module, we will take a step back and learn about tools for transforming data that might not yet be ready for visualization as well as for summarizing data with tidyverse’s data wrangling package: dplyr. In addition to describing distributions of single variables, you will also learn to explore relationships between two or more variables. Finally, you will continue to hone your data visualization skills with plots for various data types. 8 videos14 readings1 assignment2 discussion prompts1 plugin

3 modules

Beginner level

12 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/data-visualization-transformation-r

Statistical Mechanics: Algorithms and Computations

37,353

4.8

Werner Krauth

École normale supérieure

[]

In this course you will learn a whole lot of modern physics (classical and quantum) from basic computer programs that you will download, generalize, or write from scratch, discuss, and then hand in. Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach. Dear students, welcome to the first week of Statistical Mechanics: Algorithms and Computations! <br> Here are a few details about the structure of the course: For each week, a lecture and a tutorial videos will be presented, together with a downloadable copy of all the relevant python programs mentioned in the videos. Some in-video questions and practice quizzes will help you to review the material, with no effect on the final grade. A mandatory peer-graded assignment is also present, for weeks from 1 to 9, and it will expand on the lectures' topics, letting you reach a deeper understanding. The nine peer-graded assignments will make up for 50% of the grade, while the other half will come from a final exam, after the last lecture. <br> In this first week, we will learn about algorithms by playing with a pebble on the Monte Carlo beach and at the Monaco heliport. In the tutorial we will use the 3x3 pebble game to understand the essential concepts of Monte Carlo techniques (detailed balance, irreducibility, and a-periodicity), and meet the celebrated Metropolis algorithm. Finally, the homework session will let you understand some useful aspects of Markov-chain Monte Carlo, related to convergence and error estimations. 3 videos2 readings1 assignment1 peer review In Week 2, you will get in touch with the hard-disk model, which was first simulated by Molecular Dynamics in the 1950's. We will describe the difference between direct sampling and Markov-chain sampling, and also study the connection of Monte Carlo and Molecular Dynamics algorithms, that is, the interface between Newtonian mechanics and statistical mechanics. The tutorial includes classical concepts from statistical physics (partition function, virial expansion, ...), and the homework session will show that the equiprobability principle might be more subtle than expected. 3 videos1 reading1 assignment1 peer review After the hard disks of Week 2, in Week 3 we switch to clothe-pins aligned on a washing line. This is a great model to learn about the entropic interactions, coming only from statistical-mechanics considerations. In the tutorial you will see an example of a typical situation: Having an exact solution often corresponds to finding a perfect algorithm to sample configurations. Finally, in the homework session we will go back to hard disks, and get a simple evidence of the transition between a liquid and a solid, for a two-dimensional system. 3 videos2 readings1 assignment1 peer review In Week 4 we will deepen our understanding of sampling, and its connection with integration, and this will allow us to introduce another pillar of statistical mechanics (after the equiprobability principle): the Maxwell and Boltzmann distributions of velocities and energies. In the homework session, we will push the limits of sampling until we can compute the integral of a sphere... in 200 dimensions! 3 videos1 reading1 assignment1 peer review Week 5 is the first episode of a three-weeks journey through quantum statistical mechanics. We will start by learning about density matrices and path integrals, fascinating tools to study quantum systems. In many cases, the Trotter approximation will be useful to consider non-trivial systems, and also to follow the time evolution of a system. All these topics, including the matrix-squaring technique, will be reviewed in detail in the homework session, where you will also study the anharmonic potential. <br> Note that previous knowledge of quantum mechanics is not really necessary to go through the next three weeks. Follow us in our journey through algorithms and physics, and don't forget to ask on the forum if you have any doubt! 3 videos1 reading1 assignment1 peer review In Week 6, the second quantum week, we will introduce the properties of bosons, indistinguishable particles with peculiar statistics. At the same time, we will also go further by learning a powerful sampling algorithm, the Lévy construction, and in the homework session you will thoroughly compare it with standard sampling techniques. 3 videos1 reading1 assignment1 peer review At the end of our quantum journey, in Week 7, we discuss the Bose-Einstein condensation phenomenon, theoretically predicted in the 1920's and observed in the 1990's in experiments with ultracold atoms. In the path-integral framework, an elegant description of this phenomenon is in term of permutation cycles, which will also lead to a great sampling algorithm, to be discussed in the homework session. 3 videos1 reading1 assignment1 peer review In Week 8 we come back to classical physics, and in particular to the Ising model, which captures the essential physics of a set of magnetic spins. This is also a fundamental model for the development of sampling algorithms, and we will see different approaches at work: A local algorithm, the very efficient cluster algorithms, the heat-bath algorithm and its connection with coupling. All of these will be revisited in the homework session, where you will get a precise control over the transition between ordered and disordered states. 3 videos1 reading1 assignment1 peer review Continuing with simple models for spins, in Week 9 we start by learning about a dynamic Monte Carlo algorithm which runs faster than the clock. This is easily devised for a single-spin system, and can also be generalized to the full Ising model from Week 8. In the tutorial we move towards the simulated-annealing technique, a physics-inspired optimization method with a very broad applicability. You will also revisit this in the homework session, and apply it to the sphere-packing and traveling-salesman problems. 3 videos1 reading1 peer review The lecture of Week 10 includes the alpha and the omega of our course. First we repeat the experiment of Buffon's needle, already performed in the 18th century, and then we touch the sophisticated theory of Lévy stable distributions, and their connection with the central limit theorem. In the tutorial there will be time for a review of the entire course material, and then a little party is due, to celebrate the end of the course! <br> (There is no homework session for Week 10, but don't forget that the final exam is still there!) 2 videos1 reading1 assignment

10 modules

15 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/statistical-mechanics

95%

Python Classes and Inheritance

112,911

4.7

Steve Oney

University of Michigan

['Python Programming', 'Code Debugging', 'Code Testing']

This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You'll also learn how to override built-in methods and how to create "inherited" classes that reuse functionality. You'll also learn about how to design classes. Finally, you will be introduced to the good programming habit of writing automated tests for their own code. The course is best-suited for you if you are already familiar with Python fundamentals, which are covered in the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). It is optional to have taken the "Data Collection and Processing with Python" course (course 3 of the specialization), but knowledge of retrieving and processing complex nested data is helpful. This is the fourth of five courses in the Python 3 Programming Specialization. An introduction to the course 5 videos2 readings1 ungraded lab In this module, lectures and activities from the Runestone textbook will cover more complex data structures. By the end of this week, you will have learned how to process json formatted data, traverse nested data using nested iteration, and extract values from nested data. 17 videos1 assignment1 programming assignment15 app items1 ungraded lab 12 videos1 assignment1 programming assignment9 app items1 ungraded lab 17 videos2 readings3 programming assignments4 app items1 ungraded lab

4 modules

Intermediate level

https://www.coursera.org/learn/python-classes-inheritance

96%

Project Management & Other Tools for Career Development Specialization

96,907

4.7

Margaret Meloni, MBA, PMP

University of California, Irvine

['Project Management', 'Risk Management', 'Communication', 'Negotiation', 'Project Management', 'Risk Management', 'Communication', 'Negotiation']

Project management has been proven to be the most effective method of delivering products within cost, schedule, and resource constraints. It is an essential skill in the modern digital constantly changing world. This intensive and hands-on series of courses gives you a blend of skills from project management. Successful projects require careful upfront planning. In this specialization, you will gain a strong working knowledge of the basics of project management. You’ll learn the key roles and responsibilities of the project manager and project team and to answer some key questions upfront to help you meet project objectives, as well as managing project risk. Additionally, this specialization will train you in essential career success skills that have become indispensable, like business writing, negotiation and effective problem-solving. Thus, in addition to introducing you to project management, this specialization will help you build, develop and hone the essential skills needed to improve your employability and advancement in today’s dynamic workforce, giving you a complete, comprehensive skill set. Applied Learning Project Through the Project Management & Other Tools for Career Development Specialization, you will experience hands-on projects which including reviewing case studies, videos, and lectures to understand scope, stakeholder input, project communication, managing risk, document communication, negotiation, and decision making methods. Identify project stakeholders Define the role and responsibilities of the project manager Summarize the key elements of a project plan Anticipate common sources of conflict within a project environment Define components of a communications management plan Prioritize identified risks Develop responses for high-priority risks Identify and analyze changes to project scope Write effective presentations, emails, writing for visual communication Edit and proofread business documents Create business reports and press releases Spot, correct and avoid the most common writing pitfalls Understand how negotiation differs from selling Identify common negotiation styles Describe the personal and behavioral characteristics of an effective negotiator Assess your personal style and how it affects the negotiation process Explain both the affordances and limitations associated with problem-solving and decision-making Reflect on how mindset and personal bias influence your ability to solve problems and make decisions Explain and discuss how organizational decisions or non-decisions impact personal development, team dynamics, and company-wide performance Articulate how both good and bad team decisions can benefit your professional growth

5 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/project-management-success

Organizational Behavior: How to Manage People

64,866

4.7

Anneloes Raes

IESE Business School

['Management Styles', 'Leadership', 'Management', 'Organizational Culture']

Peter Drucker, a pioneer in the field of management, once said that people have a perverse tendency to behave like human beings. Of course, we are not machines, and certainly not programmable. But through the study of organizational behavior, we can gain insights into what makes people tick within a work context. Increasing your understanding of your own behavior and that of your colleagues, teams and leaders, is an important first step to bringing positive change to how you and your organization work. The objective of this course is therefore to provide insight into four key areas: • Motivation. In this course segment we will understand the concept of motivation and review various perspectives that will help you understand how we can motivate others. • Leadership. In this part of the course, we will analyze the concept of leadership and consider various perspectives and approaches to help shed light on leadership emergence and effectiveness. • Teamwork. Here we look at team functioning and effectiveness. Using the widely used input – process – output model of team effectiveness, we consider such topics as team diversity, team processes, and team outcomes. • Culture. Finally, we'll move to the level of the organization and consider the concept of organizational culture, also touching upon the concept of national culture. We look at the various ways in which culture is expressed, and discuss the implications of culture for people within organizations and cross-cultural collaborations. Welcome! Before you start today's videos, please have a look at the syllabus. In this first session, I’ll introduce you to one of the central topics of organizational behavior: motivation. We’ll explore why people act as they do so that we can better understand their motivations on the job. These insights will help you understand how managers can influence the people on their teams toward a common goal in the context of organizations. Objectives: To gain insight into human motivation from the different perspectives offered by the diverse prevailing theories in this area. 13 videos6 readings1 assignment2 discussion prompts Type the word “leadership” into Amazon’s search engine and you’ll find 150,000 related books. This is indeed a popular topic! But what is leadership really? Are leaders born or made? What traits and skills makes some people able to influence people to direct their energy towards a common objective? We will discuss all of these questions and explore some of the theories behind the study of leadership. Objective: To understand what leadership is, what makes a good leader, and how managers may develop the relevant skills to evolve in their roles. 10 videos4 readings1 assignment1 discussion prompt Teamwork is more than a business school buzz word; it’s a key element on the job today. Teams can be working side-by-side or spread across the world. What are the dynamics at play on different teams? What happens when conflict arises? Can teams evolve and overcome conflict to yield productive outcomes? This week we’ll address all of these questions to help you understand the complexity and importance of teamwork. Objective: To offer you some key insights so that you can take a step back from your own team at work and look back in with a fresh perspective. 10 videos4 readings1 assignment1 discussion prompt Culture exists on many more levels than one would immediately assume. Each organization can have a unique work culture, and this, in turn, can be greatly influenced by the country in which it operates. This week we will look at how our culture influences how we think and act on the job. Objective: To understand the crucial role culture plays in understanding people’s attitudes and actions in a work environment. 13 videos4 readings1 assignment1 peer review1 discussion prompt

4 modules

14 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/managing-people-iese

97%

Creating Features for Time Series Data

Enrollment number not found

Rating not found

Chip Wells

SAS

[]

This course focuses on data exploration, feature creation, and feature selection for time sequences. The topics discussed include binning, smoothing, transformations, and data set operations for time series, spectral analysis, singular spectrum analysis, distance measures, and motif analysis. In this course you learn to perform motif analysis and implement analyses in the spectral or frequency domain. You also discover how distance measures work, implement applications, explore signal components, and create time series features. This course is appropriate for analysts with a quantitative background as well as domain experts who would like to augment their time-series tool box. Before taking this course, you should be comfortable with basic statistical concepts. You can gain this experience by completing the Statistics with SAS course. Familiarity with matrices and principal component analysis are also helpful but not required. In this module you get an overview of the courses in this specialization and what you can expect. 1 video1 reading In this module you learn about the scope of this course and you access the software and files you will use for practices in the course. 1 video2 readings1 app item In this module, you learn about converting transactional sequences to time series. Other topics include exploring signal components in time series via decompositions and binning, and creating new time series features. 13 videos4 assignments In this module you learn about the usefulness of distance or similarity measures between time series. Calculated distance measure are used as the basis in two analyses. 8 videos5 assignments1 app item In this module, we discuss and illustrate the basic ideas and applications in frequency domain analysis. We also discuss SSA and present demonstrations of applied SSA. 11 videos6 assignments1 app item In this module you learn about detecting motifs in times series and their usefulness. 6 videos2 assignments1 app item 1 assignment

7 modules

Intermediate level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/time-series-features

AWS Data Processing and Analysis

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['AWS Glue', 'Amazon Redshift', 'AWS Data Processing', 'AWS Lambda', 'AWS OpenSearch']

This course takes you through the complete process of data handling, starting with AWS data processing services. You’ll begin with AWS Lambda, learning how to integrate serverless functions and manage scalable data pipelines. With practical exercises, you’ll explore how AWS Glue helps automate data preparation and manage complex ETL jobs, making data lake partitioning and modification of Glue Data Catalog easy to understand. Hands-on experience with Glue Studio and DataBrew will further enhance your knowledge in preparing data for analysis. The course also delves into processing large datasets using Amazon EMR, where you’ll work with Apache Spark, Hive, and other tools in the Hadoop ecosystem. You’ll learn to optimize data processing with EMR, partition and store data efficiently, and integrate it with AWS services like Kinesis and Redshift. Exercises in Apache Spark will show you how to analyze data streams and deliver actionable insights in real time. Lastly, you'll focus on the analysis aspect using services like Kinesis Analytics, OpenSearch, and Athena. The course will guide you through setting up advanced analytics using Kinesis, creating real-time monitoring applications, and visualizing data using OpenSearch and QuickSight. By the end of this course, you’ll be well-equipped to build, process, and analyze data pipelines at scale using AWS’s powerful tools. This course is ideal for data engineers, IT professionals, and data analysts aiming to leverage AWS for data processing and analysis. Some familiarity with AWS services is recommended. In this module, we will delve into AWS processing services, beginning with an introduction to AWS Lambda and Glue. You’ll learn how to integrate these tools for serverless and ETL workflows. We will also explore advanced topics such as Glue ETL job execution, Lambda's cost optimization strategies, and EMR’s integration with other AWS services like Apache Spark, Hive, and Hadoop. Hands-on exercises will cover using Spark with Kinesis and Redshift, and how to process data lakes with EMR. 35 videos2 readings In this module, we will focus on analyzing and querying data using AWS’s powerful analytics services. We begin with an introduction to Kinesis Analytics, OpenSearch, and Athena, followed by performance tuning and security best practices. Through hands-on exercises, you’ll build real-world applications to monitor data streams, optimize queries using Glue and Athena, and perform data warehousing with Redshift. Additionally, we’ll explore Redshift's durability, distribution styles, and newer features like AQUA and serverless options to improve large-scale data analytics. 32 videos1 reading1 assignment

2 modules

Intermediate level

8 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/packt-aws-data-processing-and-analysis-fezz2

Data Analytics and Databases on AWS

3,588

4.7

Rafael Lopes

Amazon Web Services

['Extraction, Transformation And Loading (ETL)', 'Data Analysis', 'Database (DBMS)', 'Data Architecture', 'Data Warehouse']

Data is everywhere. If you or your company don't know what data you have and what insights you can uncover through your data, you are at a competitive disadvantage. In this course, you'll get introduced to data analytics and the upside of data-driven decisions. You'll learn about the omnipresence of data in today's world and what it takes to start thinking and acting like a data analyst. Week 1 concludes by comparing and contrasting ETL (Extract, Transform, Load) and ELT(Extract, Load, Transform) and where data is transformed and how data warehouses retain data. Week 2 kicks off with an overview of data workflow and database foundations. The four vs (volume, velocity, variety and veracity) of data are explained along with walk-throughs of collecting, processing, and storing data. In the course's final week, you'll get briefed on some of the AWS services that can be leveraged for ETL. You'll extract data with Amazon API Gateway, process data with AWS Lambda, load data with Amazon RDS, and visualize data with Amazon QuickSight. There's the right tool for each unique data analysis task. Welcome to the first module of the course. This module introduces fundamental concepts in data analysis. You begin the module with how to assess use cases for data analysis in the cloud. Then, you explore some of the main data types and structures, and learn how metadata can help you manage datasets. Lastly, you complete the module by contrasting two data-processing approaches for analytics: extract, transform, and load (ETL) and extract, load, and transform (ELT). 8 videos7 readings2 assignments2 plugins In this module, you start learning about the ETL pipeline, with an emphasis on the real-world scenario. Through each step, you learn how to gather data, ensure data quality, locate the appropriate storage or database, and evaluate insights. After you examine the ETL process, you assess SQL and NoSQL databases, and interact with a hands-on activity to practice your skills. 7 videos2 readings1 assignment1 ungraded lab In this module, you review AWS services for data analysis, and reinforce your learning through practical labs. These services include Amazon API Gateway, Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB, and Amazon QuickSight. You review these services in the AWS Management Console, and evaluate how you can use each service in the ETL process. Then, you gain practical experience by working with some of these service in a preconfigured environment. 9 videos2 readings4 assignments3 app items1 plugin

3 modules

Beginner level

9 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/data-analytics-and-databases-aws

Accounting Analytics

112,928

4.5

Brian J Bushee

University of Pennsylvania

['Accounting', 'Analytics', 'Earnings Management', 'Finance']

Accounting Analytics explores how financial statement data and non-financial metrics can be linked to financial performance.  In this course, taught by Wharton’s acclaimed accounting professors, you’ll learn how data is used to assess what drives financial performance and to forecast future financial scenarios. While many accounting and financial organizations deliver data, accounting analytics deploys that data to deliver insight, and this course will explore the many areas in which accounting data provides insight into other business areas including consumer behavior predictions, corporate strategy, risk management, optimization, and more. By the end of this course, you’ll understand how financial data and non-financial data interact to forecast events, optimize operations, and determine strategy. This course has been designed to help you make better business decisions about the emerging roles of accounting analytics, so that you can apply what you’ve learned to make your own business decisions and create strategy using financial data. The topic for this week is ratio analysis and forecasting. Since ratio analysis involves financial statement numbers, I’ve included two optional videos that review financial statements and sources of financial data, in case you need a review. We will do a ratio analysis of a single company during the module. First, we’ll examine the company's strategy and business model, and then we'll look at the DuPont analysis. Next, we’ll analyze profitability and turnover ratios followed by an analysis of the liquidity ratios for the company. Once we've put together all the ratios, we can use them to forecast future financial statements. (If you’re interested in learning more, I’ve included another optional video, on valuation). By the end of this week, you’ll be able to do a ratio analysis of a company to identify the sources of its competitive advantage (or red flags of potential trouble), and then use that information to forecast its future financial statements. 9 videos2 readings1 assignment This week we are going to examine "earnings management", which is the practice of trying to intentionally bias financial statements to look better than they really should look. Beginning with an overview of earnings management, we’ll cover means, motive, and opportunity: how managers actually make their earnings look better, their incentives for manipulating earnings, and how they get away with it. Then, we will investigate red flags for two different forms of revenue manipulation. Manipulating earnings through aggressive revenue recognition practices is the most common reason that companies get in trouble with government regulators for their accounting practices. Next, we will discuss red flags for manipulating earnings through aggressive expense recognition practices, which is the second most common reason that companies get in trouble for their accounting practices. By the end of this module, you’ll know how to spot earnings management and get a more accurate picture of earnings, so that you’ll be able to catch some bad guys in finance reporting! 6 videos2 readings1 assignment This week, we’ll use big data approaches to try to detect earnings management. Specifically, we're going to use prediction models to try to predict how the financial statements would look if there were no manipulation by the manager. First, we’ll look at Discretionary Accruals Models, which try to model the non-cash portion of earnings or "accruals," where managers are making estimates to calculate revenues or expenses. Next, we'll talk about Discretionary Expenditure Models, which try to model the cash portion of earnings. Then we'll look at Fraud Prediction Models, which try to directly predict what types of companies are likely to commit frauds. Finally, we’ll explore something called Benford's Law, which examines the frequency with which certain numbers appear. If certain numbers appear more often than dictated by Benford's Law, it's an indication that the financial statements were potentially manipulated. These models represent the state of the art right now, and are what academics use to try to detect and predict earnings management. By the end of this module, you'll have a very strong tool kit that will help you try to detect financial statements that may have been manipulated by managers. 7 videos2 readings1 assignment Linking non-financial metrics to financial performance is one of the most important things we do as managers, and also one of the most difficult. We need to forecast future financial performance, but we have to take non-financial actions to influence it. And we must be able to accurately predict the ultimate impact on financial performance of improving non-financial dimensions. In this module, we’ll examine how to uncover which non-financial performance measures predict financial results through asking fundamental questions, such as: of the hundreds of non-financial measures, which are the key drivers of financial success? How do you rank or weight non-financial measures which don’t share a common denominator? What performance targets are desirable? Finally, we’ll look at some comprehensive examples of how companies have used accounting analytics to show how investments in non-financial dimensions pay off in the future, and finish with some important organizational issues that commonly arise using these models. By the end of this module, you’ll know how predictive analytics can be used to determine what you should be measuring, how to weight very, very different performance measures when trying to analyze potential financial results, how to make trade-offs between short-term and long-term objectives, and how to set performance targets for optimal financial performance. 8 videos2 readings1 assignment

4 modules

9 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/accounting-analytics

92%

Samsung Customer Care Essentials

Enrollment number not found

Rating not found

Amanda Harmon

Samsung

['Technical Support', 'Active Listening', 'Communication', 'Problem Solving', 'Troubleshooting']

Prepare to join a group of over 10,000 Samsung Mobile certified repair technicians in the U.S. who have gone through a training certification that equips them with the skills to conduct a mobile repair safely. Samsung has more than 1,000 Authorized Service Centers and service locations which is a care network that 75% of Americans have access to. This is an entry level course that will teach you the basics of Samsung Care that are needed to become a Samsung mobile repair technician or customer care representative. This week will focus on the background of Samsung. We will introduce the staples of Samsung devices and provide resources for a deeper understanding of what a Samsung customer may be experiencing. 4 videos10 readings1 assignment This module is all about troubleshooting devices in need of Level 1 support. 7 videos8 readings1 assignment This module details every part of the interaction with the customer. It covers customer check-in and check-out, troubleshooting, and how to prep the device for repair. 8 videos10 readings2 assignments

3 modules

Beginner level

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/samsung-customer-care-essentials

Innovation: From Creativity to Entrepreneurship Specialization

34,675

4.8

Raj Echambadi

University of Illinois Urbana-Champaign

['Business Model', 'Creativity', 'Innovation', 'Entrepreneurship', 'Innovation Management']

In a world characterized by volatility, uncertainty, complexity, and ambiguity, leaders require robust innovation skills. Thinking flexibly and developing an entrepreneurial mindset are critical to thriving in uncertain business environments. This specialization addresses how to recognize and question assumptions and constraints to identify and capitalize on opportunities. Learning to change the rules of the game by creating innovative value propositions and discovering new market positions for sustained competitive advantage are some of the actionable lessons in this specialization. This specialization will be of value to both aspiring and practicing entrepreneurs as well as employees in established firms who are interested in becoming innovative leaders in an interconnected world. This specialization is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admissions into the programs and explore how your Coursera work can be leveraged if accepted into a degree programhereOpens in a new tab. Applied Learning Project The capstone for the specialization will provide a learning experience that integrates across all the courses within it. It will involve analysis of a situation concerning a new enterprise – a venture of one’s own or within a larger organization – to develop the current business model and compare against alternative business models so as to identify potential opportunities and challenges. Innovation strategy is about creating unique value for consumers by delivering a great product that satisfies their needs. This course introduces the fundamental strategy concepts and tools that enable firms to manage technological innovations for competitive advantage. It does so by first considering the sources of technological change and how to leverage technologies to create firm value. It then examines the various mechanisms for extracting value from technologies, both legal (e.g., patents, trade secrecy, etc.) and strategic (e.g., lead time, complementary assets, etc.). We will explore the fundamentals of technology strategy through readings and case studies in both established and entrepreneurial firms across a range of technology-based industries. You will be able to: - Learn fundamental strategy concepts and frameworks for technology-based firms - Apply theories and frameworks toward the analysis and formulation of strategies for creating and capturing value through technological innovations - Develop an ability to think strategically and make decisions under uncertainty and risk - Develop skills in performing analytic research and preparing professional reports - Develop skills in managing diverse teams and working under time and resource constraints This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. You may have noticed that what is new often behaves differently than what has become accepted over time whether it is in a market, technology, or with people and firms. This course helps you develop a perspective on managing innovation. That is, you will build your capability to lead and design your organization in effectively implementing innovation initiatives and achieving their strategic intent. To do this, you will learn a set of frameworks, tools, and concepts that can help you address several important challenges in managing innovation. The first challenge is in regards to how to successfully implement innovation efforts within established firms and alongside established businesses. You then investigate the particulars of managing innovation when disruptive technologies are involved. Other topics include leadership of new product development teams, planning and evaluation of innovation initiatives, and management of innovation across organizational boundaries, as happens with alliances or virtual firms. You will be able to: - Analyze innovations and their impact on organizations - Articulate a research-informed perspective on innovation - Utilize frameworks, tools, and concepts to address challenges that arise in innovation This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. Thinking and doing the same things faster and better is not enough for innovation; we need creativity. Fortunately, creativity is a skill you can learn. This course will examine when, why, and how you can be creative so you can go through the creative process more efficiently and effectively. It teaches concrete steps to enable you to change your perspective to see new possibilities and solutions. It clarifies what to expect from the creative process and provides support for how you can sustain your progress. It also provides guidance on leading a supportive culture for creativity. The result is an ability to increase your own creativity and that of your teams and organizations so as to recognize and develop new opportunities. You will be able to: - Identify and generate opportunities to be creative and launch the innovation process - Intentionally and confidently enter and proceed through the creative process - Foster and sustain the creativity of others This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. Creativity requires us to collaborate with others, and this course helps you be a better creative collaborator. We need to be able to pitch our creative ideas so that others are excited rather than baffled or dismissive by them. We need to be able to evaluate the ideas of others so we identify rather than miss creative solutions. We need to be able to work with our teams such that creativity thrives rather than is suppressed. This course addresses each of these needs, identifying challenges and providing guidance for effective performance. The end result is guidance on how to foster effective creative collaboration. You will be able to: -Design pitches for innovative ideas to build excitement and clarity -Evaluate the pitches of others to identify great new ideas -Lead groups to foster effective collaboration for innovation This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. This course will explore the earlier stages of the entrepreneurial venture process across four modules. The modules will examine the nature of growth and error in entrepreneurial settings and how to manage resources in those settings. In addition, the modules will explore the emergence of entrepreneurial opportunities, the formulation of ideas in relation to those opportunities, and how those opportunities and ideas influence entrepreneurial phenomena. Finally, the course will focus on how business concepts underlie compelling entrepreneurial missions that provide guidance to the evolution of a venture’s business model and future strategic planning. You will be able to: - Develop a foundational understanding of the entrepreneurial process - Consider the relationship between growth and error - Understand how particular opportunities influence entrepreneurial phenomena This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. This course builds on previous concepts and outlines strategies and tactics for forming, financing, and launching a new venture. Topics to be addressed will include building the new venture’s initial management team, identifying and reaching out to early customers, developing financial plans, raising startup and initial growth financing, and preparing for and managing rapid growth. You will be able to: - Develop an understanding of what is required in a new venture - Create a plan to identify and approach your first customers - Build financial projections for the new venture - Understand how to raise equity capital for the new venture - Monitor the health and scalability of a new venture This course is part of Gies College of Business’ suite of online programs, including the iMBA and iMSM. Learn more about admission into these programs and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. The capstone for the specialization will provide a learning experience that integrates across all the courses within it. It will involve analysis of a situation concerning a new enterprise – a venture of one’s own or within a larger organization – to develop the current business model and compare against alternative business models so as to identify potential opportunities and challenges.

7 course series

Beginner level

3 months (at 10 hours a week)

https://www.coursera.org/specializations/innovation-creativity-entrepreneurship

Providing Social, Emotional, Behavioral, and Special Education Services in School

21,682

4.8

Eve Kutchman

University of Colorado System

[]

Welcome to our the third course in the School Health specialization: Providing Social, Emotional, Behavioral, and Special Education Services in School. In this course, you will learn about how social-emotional skills, mental health, and learning are related. We will focus on how schools can support social-emotional learning and promote mental health for all students. We will walk through the reasons that schools should promote student mental health. Next, we’ll review school wide activities to support skill development and prevent social, emotional, and behavioral challenges. Then, we’ll identify strategies for students at risk of developing problems. Finally, we’ll highlight interventions that can be used for students who have significant mental health needs. We will emphasize the ways that schools think about mental health problems and provide services for students with disabilities, which is different than in medical or mental health settings. As part of the course, we will introduce two students to help all of this information come alive. Prepare yourself to learn about an essential piece of student wellness—social-emotional health. In the next few lessons, you will learn broadly about the relationship between student health and learning. We will take a deeper dive to explore the relationship between mental health and learning. You will be introduced to a model schools can use to promote student mental health. Finally, you will meet two students – Kelsey and Javier. We will follow Kelsey and Javier throughout the entire course to illustrate the different supports available to promote student mental health and learning. 5 videos4 readings1 assignment In this module we will learn about interventions that all students can receive to promote social-emotional well being and prevent mental health problems. You will learn about different ways that schools can promote a positive environment, teach social-emotional skills, respond to diverse learners, support students exposed to trauma, and prevent bullying and suicide. 6 videos6 readings1 assignment in this module we will learn about strategies that schools use for some students who are at risk of developing social-emotional or behavioral problems. We will discuss how schools create plans and monitor the success of these interventions using data. We will provide examples of different approaches that schools can use depending on the student’s area of need, including interventions for behavior problems, social skills, bullying, and coping. 5 videos5 readings1 assignment In these final lessons, you will learn about the most intensive levels of support meant for few students with significant social-emotional or behavioral challenges. You will also learn about how students with identified special needs may also be eligible for individualized supports through 504 plans and/or Individualized Education Plans. Finally, you will find out what happened with our students - Kelsey and Javier! 5 videos3 readings1 assignment

4 modules

Beginner level

https://www.coursera.org/learn/providing-social-emotional-behavioral-and-special-education-services-in-school

98%

Serverless Data Processing with Dataflow: Develop Pipelines

4,050

4.0

Google Cloud Training

Google Cloud

[]

In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks. This module introduces the course and course outline 1 video1 reading Review main concepts of Apache Beam, and how to apply them to write your own data processing pipelines. 4 videos1 reading1 assignment2 app items In this module, you will learn about how to process data in streaming with Dataflow. For that, there are three main concepts that you need to learn: how to group data in windows, the importance of watermark to know when the window is ready to produce results, and how you can control when and how many times the window will emit output. 3 videos1 reading1 assignment4 app items In this module, you will learn about what makes sources and sinks in Dataflow. The module will go over some examples of Text IO, FileIO, BigQueryIO, PubSub IO, KafKa IO, Bigtable IO, Avro IO, and Splittable DoFn. The module will also point out some useful features associated with each IO. 8 videos1 reading1 assignment This module will introduce schemas, which give developers a way to express structured data in their Beam pipelines. 2 videos1 reading1 assignment2 app items This module covers State and Timers, two powerful features that you can use in your DoFn to implement stateful transformations. 3 videos1 reading1 assignment This module will discuss best practices and review common patterns that maximize performance for your Dataflow pipelines. 7 videos1 reading1 assignment2 app items This modules introduces two new APIs to represent your business logic in Beam: SQL and Dataframes. 3 videos1 reading1 assignment4 app items This module will cover Beam notebooks, an interface for Python developers to onboard onto the Beam SDK and develop their pipelines iteratively in a Jupyter notebook environment. 1 video1 reading1 assignment This module provides a recap of the course 1 video

10 modules

Advanced level

31 hours to complete (3 weeks at 10 hours a week)

https://www.coursera.org/learn/developing-pipelines-on-dataflow

Introduction to Corporate Communications

2,158

4.6

Chris Ruoff

University of California, Irvine

['Business Communication', 'Dynamic Communication', 'Tactical Communications', 'Communication Strategies', 'Project Communications']

Discover the fundamental principles of corporate communications in this introductory course by learning about the significance of transparent communication, the art of storytelling, and the power of social media tools. Learn practical strategies to engage employees, whether they work in-person, remote, or hybrid. Additionally, gain insights into the personality types that tend to excel in different corporate communication careers, allowing you to align your strengths and interests with the right professional trajectory. Welcome to Module 1, The Role of Corporate Communications. This module will introduce corporate communications, define the roles and responsibilities in corporate communications, and explain the importance of transparency. 1 video2 readings1 assignment1 discussion prompt Welcome to Module 2, Corporate Communication Tools. This module will introduce which tools are used to communicate in both internal and external environments as well as the types and uses of each. 3 videos2 readings1 assignment1 discussion prompt1 plugin Welcome to Module 3, Communicating in Hybrid Work Environments. This module will discuss the emergence of hybrid work environments, how corporate communications are essential to engaging the workforce, and what tools to use. 1 video2 readings1 assignment1 discussion prompt Welcome to Module 4, Corporate Communications as a Career. This module will look at career opportunities in corporate communications, including which specific jobs are available, possible career paths, and entry requirements into the field. 2 videos2 readings1 assignment1 discussion prompt

4 modules

Beginner level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/introduction-to-corporate-communications

Splunk Query Language and Data Analysis

Enrollment number not found

Rating not found

EDUCBA

EDUCBA

['Splunk Dashboards and Reporting', 'Advanced Threat Detection and Hunting', 'Threat Intelligence Integration in Splunk Security Essentials', 'Customising SSE App', 'Advanced SPL Techniques']

The "Splunk Query Language and Data Analysis" course equips you with fundamental skills to effectively use Splunk, a powerful platform for managing machine-generated data. Whether you're an experienced IT professional or new to data analysis, this course provides a foundational understanding of Splunk's query language and data analysis capabilities. Learning Objectives: 1) Understand essential basic commands, create and utilize custom fields, and transform data 2) Understand the concept of macros in SPL, advanced statistical functions, and advanced data manipulation techniques 3) Learn how to design and build interactive dashboards, understand the importance of scheduled searches and alerts, gain proficiency in creating and customizing Splunk reports By the end of the course, you will be able to: • Recognize basic SPL commands like search, eval, and stats for data analysis • Discover data transformation and calculated field creation with the eval command • Formulate and apply custom fields, tags, and event types for efficient data categorization • Examine advanced SPL techniques for complex data transformations and statistical analysis • Apply time-based analysis with functions like time-chart, chart and event-stats • Manipulate complex data structures and nested fields • Use macros to simplify complex queries and promote reusability • Design interactive, visually appealing dashboards in Splunk using the dashboard editor • Compile Splunk reports for effective presentation of search results • Schedule searches and alerts for proactive data monitoring and notifications Module 1: Introduction to SPL (Splunk Query Language) Description: The “Introduction to SPL (Splunk Query Language)" module provides an overview of the essential concepts and syntax of SPL, the powerful query language used in Splunk. You will gain a foundational understanding of how to construct searches, filter and transform data, use functions for aggregation, and visualize results, enabling them to extract valuable insights and analyze data effectively within the Splunk platform. You will demonstrate essential basic commands like search, eval, and stats, allowing you to perform simple data analysis tasks and retrieve specific information from the data. You will Identify how to transform data and compose calculated fields using the eval command, developing data analysis and enabling the discovery of valuable insights. You will identify, compose and utilize custom fields, tags, and event types, enabling you to categorize and enhance data for more efficient analysis and visualization. Module 2: Advanced SPL Techniques Description: The "Advanced SPL Techniques" module delves into more sophisticated and powerful techniques in the Splunk Query Language (SPL). You will explore complex data transformations, advanced statistical and time-based functions, subsearches, and joint operations to perform intricate data analysis tasks. You will demonstrate to leverage the full potential of SPL, allowing you to tackle complex data scenarios and gain deeper insights from their data in the Splunk platform. You will Illustrate advanced statistical functions like timechart, chart, and eventstats in SPL to perform complex data aggregations and time-based analysis. Discover advanced data manipulation techniques in SPL, such as multikv, spath, and streamstats, to handle complex data structures and nested fields effectively. Identify the concept of macros in SPL and how to create and use them to simplify complex queries and promote reusability. Module 3: Splunk Dashboards and Reporting Description: The "Splunk Dashboards and Reporting" module focuses on teaching you how to design and create interactive and visually appealing dashboards in Splunk. You will design search results, visualizations, and custom components to present data insights effectively. Furthermore, the module covers various reporting techniques to generate scheduled and ad-hoc reports, enabling users to share critical information with stakeholders and make informed decisions. You will learn how to design and build interactive and visually appealing dashboards in Splunk using the dashboard editor. Gain proficiency in creating and customizing Splunk reports to present search results in tabular format effectively. Identify the importance of scheduled searches and alerts for proactive data monitoring and event-driven notifications. Target Learners: This course is suitable for IT professionals, data analysts, and anyone interested in harnessing the power of Splunk for data analysis and insights. Learner Prerequisites: Basic understanding of Splunk is required, along with a basic understanding of data analysis concepts is an added advantage. Reference Files: You will have access to code files in the Resources section. Course Duration: The course spans three modules, with each module designed to be completed in approximately 3-4 weeks, depending on individual learning pace. The ""Introduction to SPL (Splunk Query Language)"" module provides an overview of the essential concepts and syntax of SPL, the powerful query language used in Splunk. Learners will gain a foundational understanding of how to construct searches, filter and transform data, use functions for aggregation, and visualize results, enabling them to extract valuable insights and analyze data effectively within the Splunk platform." 11 videos5 readings4 assignments1 discussion prompt The "Advanced SPL Techniques" module delves into more sophisticated and powerful techniques in the Splunk Query Language (SPL). Learners will explore complex data transformations, advanced statistical and time-based functions, subsearches, and join operations to perform intricate data analysis tasks. This module empowers users to leverage the full potential of SPL, enabling them to tackle complex data scenarios and gain deeper insights from their data in the Splunk platform. 12 videos2 readings4 assignments1 discussion prompt The "Splunk Dashboards and Reporting" module focuses on teaching learners how to design and create interactive and visually appealing dashboards in Splunk. Participants will learn to combine search results, visualizations, and custom components to present data insights effectively. Additionally, the module covers various reporting techniques to generate scheduled and ad-hoc reports, enabling users to share critical information with stakeholders and make informed decisions. 12 videos3 readings4 assignments1 discussion prompt

3 modules

Intermediate level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/splunk-query-language-and-data-analysis

Generative AI with Large Language Models

312,484

4.8

Chris Fregly

DeepLearning.AI

['Python Programming', 'Machine Learning', 'Large Language Models', 'LLMs', 'Generative AI']

In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications. By taking this course, you'll learn to: - Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment - Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases - Use empirical scaling laws to optimize the model's objective function across dataset size, compute budget, and inference requirements - Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project - Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology. This is an intermediate course, so you should have some experience coding in Python to get the most out of it. You should also be familiar with the basics of machine learning, such as supervised and unsupervised learning, loss functions, and splitting data into training, validation, and test sets. If you have taken the Machine Learning Specialization or Deep Learning Specialization from DeepLearning.AI, you’ll be ready to take this course and dive deeper into the fundamentals of generative AI. Generative AI use cases, project lifecycle, and model pre-training 17 videos7 readings1 assignment2 app items Fine-tuning and evaluating large language models 10 videos3 readings1 assignment1 app item Reinforcement learning and LLM-powered applications 21 videos7 readings1 assignment1 app item

3 modules

Intermediate level

https://www.coursera.org/learn/generative-ai-with-llms

95%

Esports Specialization

5,490

4.6

Stephane Muller

University of California, Irvine

['Management', 'Esports', 'Events', 'Production', 'Gaming']

The Esports Management Specialization prepares students to turn a passion for gaming into a viable career. According to a market report by Newzoo, global esports revenues have reached $906 million in 2018, a year-on-year growth of +38%. Speak knowledgeably about the history, community, and business of esports with future employers and other stakeholders in the industry. Individuals aspiring to launch or already beginning their career in the business of esports. This program suits game developers, finance professionals, community managers, marketers, and project managers. Overview of esports will introduce learners to the roles and influences that game developers have in the industry. Learners get a glimpse into the structures of an organization and how it builds a brand. Learners will also be informed of the jobs available in esports and where to get started in order to be involved. Applied Learning Project We will analyze the pros and cons of creating a single or multiple Esport organization and recommend an effective branding strategy for a hypothetical Esport organization based on current Esport branding considerations. You will develop a plan for recruiting funding resources for a hypothetical Esports organization and choose an Esport organization role of interest, other than Owner, and describe your reasoning. Before you can have an Esport, you must have a video game to play and a game developer to design it. This course is dedicated to discussing game developers and their relationship with their respective Esport. The content will help you recognize the qualities a video game must have to become a successful Esport. We will examine the diagram demonstrating the various competitive structures commonly found in Esports. Esports, just like traditional sports, have their own professional organizations. These organizations strive to become successful businesses that win, make a profit, take care of their professional players, and attract a large audience. We will explore the factors that contribute to an Esports organization’s success, including branding, positioning, structuring the organization and funding sources. This course will be focusing on the competitive Esport team and individual professional players. Whether you are playing on a team or competing as an individual, you will find that being a professional Esports player is more complex and nuanced than most people realize. We will be talking a lot about the support staff surrounding players, the intricacy of navigating contracts, and the hardships of committing yourself to professional play. We will also be talking about the Esports media. Similar to sports, Esports has developed its own unique ecosystem of articles, videos, streaming, social media, and overall content creation. We will examine the specifics of different types of media and explain how each has its uses in making Esports more popular as a whole. This course will be covering hot topics in the Esports industry. With Esports exploding in popularity over the last ten years, there are a lot of issues to discuss. We will also be talking about collegiate Esports and career planning in order to understand all the different avenues and to examine the choices available for you as you pave your way through the Esports world. We will examine collegiate Esports, as that is generally the first step, but we will be covering general career planning too. We will analyze the pros and cons of creating a single or multiple Esport organization and recommend an effective branding strategy for a hypothetical Esport organization based on current Esport branding considerations. You will develop a plan for recruiting funding resources for a hypothetical Esports organization and choose an Esport organization role of interest, other than Owner, and describe your reasoning.

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/esports

Try RRI! A guide for Responsible Research and Innovation

Enrollment number not found

Rating not found

Margit Hofer

University of Amsterdam

[]

In this online course you will learn how to apply Responsible Research and Innovation (RRI) in your own work. First by understanding why it is important to act responsibly in your research and innovation processes at all. In a second step, you will get introduced to several tools that will help make your own work in research and/or innovation more aware by introducing concepts of RRI. In addition, we will present inspiring examples and cases from the NewHoRRIzon RRI pilots, which effectively applied RRI in different sciences. Finally, you will see how you can consider R&I processes from different viewpoints by conducting exercises. Welcome to our course on Responsible Research and Innovation! In this online course, you will learn about why it is important to act responsibly in your research and innovation processes and reflect on the different fields of application. You will get introduced to several tools that will help make your own work in research and/or innovation more aware by introducing concepts of RRI and related issues to your work or study settings. In addition, we will present inspiring examples and cases from the NewHoRRIzon RRI pilots, which effectively applied RRI in different sciences. Finally, you will see how you can consider R&I processes from different viewpoints by conducting exercises. This course is specifically customized for researchers and students, innovators, policymakers as well as interested people from personal development, education and innovation trainers. 1 video1 reading1 discussion prompt In this lecture, you will learn what RRI exactly is and why it has become so important for today's society. 1 video3 readings2 assignments1 discussion prompt Now it's time to go into practice! Thus, in this module, you will get to know several tools that will help you reflect and integrate RRI in your daily work. Consequently, this section will be very practical and we will ask you to test and experiment with three different tools that can help you to analyse your research and innovation process. Experimenting with these tools will help you gain the practical know-how needed to quickly and powerfully apply these techniques to your daily work. 1 video2 readings1 discussion prompt In this module, you will learn about the effective techniques of Social labs which helps apply RRI in groups, gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about the theoretical underpinnings of Social Labs, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. This module will also draw from numerous case studies and applications so that you will learn how to apply RRI in collaboration and be inspired for your own RRI practice. 4 videos4 readings1 assignment Yes, we can! In this last module we will show you different examples, outputs and the personal gains of participants from RRI integration through Social Labs. At the end of this module, you will be asked to design your own future plan for RRI in your working environment and to take a small test about how you plan to do so. 3 videos2 readings1 assignment

5 modules

Beginner level

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/newhorrizon

Building No-Code Apps with AppSheet: Foundations

8,245

4.7

Google Cloud Training

Google Cloud

['Work with app data sources using Google sheets', 'Understand the capabilities of the AppSheet no-code app development platform', 'Navigate the AppSheet UI and editor to build an app']

In this course you will learn the fundamentals of no-code app development and recognize use cases for no-code apps. The course provides an overview of the AppSheet no-code app development platform and its capabilities. You learn how to create an app with data from spreadsheets, create the app’s user experience using AppSheet views and publish the app to end users. Introducing the AppSheet course. 1 video Define the fundamentals of no-code app development and provide an overview of AppSheet capabilities. 7 videos1 reading1 assignment How to get started using AppSheet and understand the AppSheet editor user interface. 8 videos1 assignment1 app item Using data sources with your app. 7 videos1 assignment1 app item Using the AppSheet editor define the user experience of the app. 7 videos1 assignment1 app item Describe the app publication process. 7 videos1 assignment1 app item Review the Building No-Code Apps with AppSheet: Foundations course. 1 video

7 modules

Beginner level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/building-no-code-apps-with-appsheet-foundations

Blockchain in Financial Services: Strategic Action Plan

6,713

4.4

Don Tapscott

INSEAD

[]

In this fourth and final course of the specialization, you will synthesize your learning into a Strategic Action Plan. The goals of this course are twofold: One, it’s for you to identify a specific need or problem within the financial services industry that can potentially be solved using blockchain technology. Two, it’s for you to investigate possible solutions to this problem, and to develop a strategic plan for how these solutions might be executed. You will accomplish different project milestones each week, and will be introduced to several tools to organize your findings. Throughout this process, you will hear from real-world practitioners who have hands-on experience in the blockchain ecosystem. Additionally, by participating in this course you will gain access to our Blockchain Case Commons—a crowdsourced collection of blockchain applications and use-cases spanning multiple industries. As an outcome of this course, you will walk away with a consolidated, peer-reviewed Strategic Action Plan, which you can use to pitch your idea to your organization and/or potential investors. Almost every industry can expect to experience a major business model disruption as blockchain technologies take hold. In this module, you will explore current applications of blockchain in the financial services industry, and will perform some preliminary market research in order to identify a specific market segment that shows promise for blockchain technologies. Throughout this process, you will use and contribute to our Blockchain Case Commons, which will serve as a shared, continuously-evolving repository of blockchain applications and use-cases for all course participants. 6 videos5 readings1 assignment1 peer review1 discussion prompt2 plugins When identifying opportunities for blockchain technology within your chosen market, it is important to understand the kinds of problems that it can and cannot solve—at least in its current state. In this module, you will learn to distinguish between problems that are and are not well-suited to blockchain-based solutions. After considering various opportunities for blockchain technology within your chosen market segment, you will use a decision matrix to select the most promising idea to pursue for your final project. By the end of this week, you will clarify the purpose and objectives of your project, you will identify your target customers/audience, and you will prepare a statement of need and statement of benefit for your proposal. 11 videos6 readings1 peer review1 discussion prompt1 plugin In the last module, you identified a promising idea or opportunity for blockchain within your chosen market segment. This week, you will work on positioning your idea—carving out a niche or identity for your product/service within the minds of your target customers. By the end of this week, you will explain how your idea will bring new or added value to your customers, and how your idea will affect the positioning for your organization. 2 videos2 readings1 peer review1 plugin An idea may seem great on paper, however actually executing this idea will require careful consideration of various strategic decisions, including those related to funding, risk, talent, timing, corporate boundaries, and partners/allies. In this module, you will begin to think about what would be required to transform your project from idea to reality. 3 videos5 readings1 peer review So far in this course you have performed an industry analysis, selected a specific market segment, assessed your competition, and identified a promising opportunity for blockchain within your chosen market. As well, you have described how you will position your idea, and have given consideration to the strategic decisions that need to be made in order to transform your idea into reality. In this final module, you will consolidate all of the work you have produced thus far into a final, peer-reviewed project deliverable, which you can use to pitch your idea to your organization and/or potential investors. 3 videos1 peer review

5 modules

Intermediate level

14 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/blockchain-strategic-action-plan

Intellectual Humility: Practice

14,177

4.7

Dr. Ian Church

The University of Edinburgh

[]

We live in a polarised world where all too often people talk past each other. But do you know when to believe what others say? For example, how quick should we be to accept something that someone else tells us is true, and what should we be looking out for when assessing a person's trustworthiness? Meanwhile, what should we do when we encounter disagreements with people who seem to be our equals? How and when should we adjust our beliefs, and how does the appropriate response vary depending on the evidence? These challenges may be especially important in the arena of religious disagreements. How should we weigh the evidence for and against various theistic and atheistic stances? Experts in psychology, philosophy, theology and education are conducting exciting new research on these questions, and the results have important, real-world applications. Faced with difficult questions people often tend to dismiss and marginalize dissent. Political and moral disagreements can be incredibly polarizing, and sometimes even dangerous. And whether it’s Christian fundamentalism, Islamic extremism, or militant atheism, religious dialogue remains tinted by arrogance, dogma, and ignorance. The world needs more people who are sensitive to reasons both for and against their beliefs, and are willing to consider the possibility that their political, religious and moral beliefs might be mistaken. The world needs more intellectual humility. In this course. we will examine the following major questions about applied issues surrounding intellectual humility: • Should you believe what people say? • How should we handle disagreement? • What is the role of evidence in resolving religious disagreements? All lectures are delivered by leading specialists, and the course is organised around a number of interesting readings and practical assignments which will help you address issues related to humility in your daily life. This course can be taken as a part of a series which explores the theory, the science and the applied issues surrounding intellectual humility. Before, we considered how to define and measure intellectual humility, what intellectual virtue is, whether we are born or can become humble, and what cognition and emotions can tell us about intellectual humility. If you are interested, complete all three courses to gain a broader understanding of this fascinating topic. Look for: • Intellectual Humility: Theory - https://www.coursera.org/learn/intellectual-humility-theory • Intellectual Humility: Science - https://www.coursera.org/learn/intellectual-humility-science Check out our trailer to hear more - https://youtu.be/x_CWjrYxKZU. 1 video3 readings1 discussion prompt Professor Peter Graham points out that a great deal of what we know, we know because other people told us. But can we always believe them? Should we be trusting, or sceptical? The truth lies somewhere in the middle. This lecture will offer you some guidelines on how to find it, and on how to avoid the pitfalls created by our fears, biases, and over-confidence. 8 videos8 readings6 assignments4 discussion prompts Resolving disagreements may seem easy when one person clearly knows more about the topic of disagreement than the other. But what about cases where both parties are equally knowledgable and capable - in other words, when they are intellectual equals? Professor Catherine Elgin discusses various strategies we can adopt, and helps us understand how people who have the same evidence and reasoning ability can still disagree. 4 videos7 readings7 assignments4 discussion prompts Dr Katherine Dormandy explains why religious disagreements are so often particularly hard to resolve. Distinguishing between two types of evidence one can have in religious discussions - public and private - she evaluates three Evidence Weighting Policies we can use in determining how to approach others when talking about religion. 8 videos5 readings6 assignments4 discussion prompts 6 readings1 peer review1 discussion prompt

5 modules

Beginner level

https://www.coursera.org/learn/intellectual-humility-practice

96%

Business Intelligence and Visual Analytics

3,526

4.1

Tim Carrington

University of California, Irvine

['Business Intelligence', 'Data Warehousing', 'Data Visualization', 'SAS Visual Analytics', 'SAS Viya']

Building on “Data Warehousing and Business Intelligence,” this course focuses on data visualization and visual analytics. Starting with a thorough coverage of what data visualization is and what type of visualization is good for a given purpose, the course quickly dives into development of practical skills and knowledge about visual analytics by way of using one of the most popular visual analytics tools: SAS Viya, a cloud-based analytics platform. An overview of cloud architecture, automation, and machine learning is also provided. Welcome to Module 1, Data Visualization and Visual Analytics. In this model, we will go over the need for data visualization in business reporting. We will identify the benefits of data visualization as well as differentiate between types of data visualizations. We will also overview visual analytics and the landscape of visual analytics tools. Finally, in our activity, we will describe an effective visualization and how to derive value and insight based on available data points. 6 readings1 quiz1 discussion prompt Welcome to Module 2, Visual Analytics Basics and SAS Viya Platform. This module provides an introduction to SAS Visual Analytics and SAS Viya. Through this module, we will identify the phases and select the features of SAS Visual Analytics. In our activity, we will identify the types of reports that could be useful for specific datasets. We will also describe the import process for datasets in SAS Data studio. 3 videos1 reading1 quiz1 discussion prompt Welcome to Module 3, Developing Advanced Visualizations with SAS Viya. Through this module, we will go over how to use SAS Viya to create data visualizations. We will identify key features and functions of SAS Visual Analytics. We will also learn key functions in SAS and be able to differentiate between their functionalities. Finally, in our activity, we will create interactive data reports and describe the value and insights that can be derived from data reports. 4 videos1 reading1 quiz1 discussion prompt Welcome to Module 4, Advanced Business Intelligence and Data Warehousing Topics. In this final module, we will define machine learning, identify the key enablers of big data, and list the advantages of cloud-based architectures. Our course (and specialization) culminates in this module’s graded assignment. In it, we will design and implement a dashboard in SAS Visual Analytics, tell a cohesive story through data, and derive insights from interaction on a visualization dashboard. We will also practice our new skills in visual analytics by peer reviewing other’s dashboards. 4 readings1 quiz1 peer review

4 modules

Intermediate level

12 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/business-intelligence-visual-analytics

Google AI Essentials

775,242

4.7

Google Career Certificates

Google

['Artificial Intelligence (AI)', 'Large Language Models (LLMs)', 'Prompt Design', 'Generative AI']

Google AI Essentials is a self-paced course designed to help people across roles and industries get essential AI skills to boost their productivity, zero experience required. The course is taught by AI experts at Google who are working to make the technology helpful for everyone. In under 10 hours, they’ll do more than teach you about AI — they’ll show you how to actually use it in the real world. Stuck at the beginning of a project? You’ll learn how to use AI tools to generate ideas and content. Planning an event? You’ll use AI tools to help research, organize, and make more informed decisions. Drowning in a flooded inbox? You’ll use AI tools to help speed up those daily work tasks, like drafting email responses. You’ll also learn how to write effective prompts and use AI responsibly by identifying AI’s potential biases and avoiding harm. After you complete the course, you’ll earn a certificate from Google to share with your network and potential employers. By using AI as a helpful collaboration tool, you can set yourself up for success in today’s dynamic workplace — and you don’t even need programming skills to use it. Discover how AI works and explore foundational AI concepts, such as machine learning (ML). Learn about the rise of generative AI and how to perform tasks with it. By the end of this module, you’ll have an understanding of the capabilities and limitations of AI tools and how to integrate generative AI in the workplace. 11 videos4 readings2 assignments1 plugin Leverage generative AI tools to speed up work tasks and boost your productivity. Examine the important role humans play in the effective use of AI, and understand the types of workplace tasks you can augment with AI. By the end of this module, you will be able to determine if AI is right for a given task and how to use AI to accelerate workflows. 11 videos5 readings3 assignments Write effective prompts to get the output you want. Learn how to incorporate prompting techniques, such as few-shot prompting, into your work. Understand how generative AI tools produce output and the importance of evaluating output before using it. By the end of this module, you will be able to write clear and specific prompts and produce outputs that help accomplish workplace tasks. 9 videos5 readings3 assignments1 plugin Use AI responsibly by mitigating unfair biases and inaccuracies. Learn how to apply a framework of AI harms to sample workplace scenarios and recognize the security risks of using AI in the workplace. By the end of this module, you will gain an understanding of how to use AI responsibly and effectively, and a checklist to help you do it. 8 videos2 readings1 assignment Continue developing your skills within the current and emerging AI landscape. Learn about the ways organizations have leveraged AI and consider how these innovations may inspire your own AI-powered workplace solutions. By the end of this module, you will develop a strategy to stay up-to-date with future AI developments. 9 videos4 readings3 assignments1 plugin

5 modules

Beginner level

https://www.coursera.org/learn/google-ai-essentials

98%

Biology Meets Programming: Bioinformatics for Beginners

191,942

4.2

Pavel Pevzner

University of California San Diego

['Bioinformatics', 'Bioinformatics Algorithms', 'Biology', 'Python Programming']

Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction to our Bioinformatics Specialization (https://www.coursera.org/specializations/bioinformatics), preparing learners to take the first course in the Specialization, "Finding Hidden Messages in DNA" (https://www.coursera.org/learn/dna-analysis). Each of the four weeks in the course will consist of two required components. First, an interactive textbook provides Python programming challenges that arise from real biological problems. If you haven't programmed in Python before, not to worry! We provide "Just-in-Time" exercises from the Codecademy Python track (https://www.codecademy.com/learn/python). And each page in our interactive textbook has its own discussion forum, where you can interact with other learners. Second, each week will culminate in a summary quiz. Lecture videos are also provided that accompany the material, but these videos are optional. Where in the Genome Does Replication Begin? (Part 1) 2 videos2 readings1 assignment1 app item Where in the Genome Does Replication Begin? (Part 2) 2 videos1 reading1 assignment1 app item Which DNA Patterns Play the Role of Molecular Clocks? (Part 1) 3 videos1 reading1 assignment1 app item Which DNA Patterns Play the Role of Molecular Clocks? (Part 2) 3 videos1 reading1 assignment1 app item

4 modules

Beginner level

https://www.coursera.org/learn/bioinformatics

94%

Fundamentals of Graphic Design

803,527

4.8

Michael Worthington

California Institute of the Arts

['Creativity', 'Graphics', 'Design Theory', 'Color Theory']

Graphic Design is all around us! Words and pictures—the building blocks of graphic design—are the elements that carry the majority of the content in both the digital world and the printed world. As graphic design becomes more visible and prevalent in our lives, graphic design as a practice becomes more important in our culture. Through visual examples, this course will teach you the fundamental principles of graphic design: imagemaking, typography, composition, working with color and shape... foundational skills that are common in all areas of graphic design practice. I don't just want you to watch a video of someone talking about design, I want you to MAKE design! If you want to be a designer you have to be a maker and a communicator, so this course will offer you lots of opportunities to get your hands dirty with exercises and with more practical projects. At the end of this course you will have learned how to explore and investigate visual representation through a range of image-making techniques; understand basic principles of working with shape, color and pattern; been exposed to the language and skills of typography; and understand and have applied the principles of composition and visual contrast. If you complete the course, along with its optional (but highly recommended) briefs, you will have a core set of graphic design skills that you can apply to your own projects, or to more deeply investigate a specialized area of graphic design. To succeed in this course you will need access to a computer. You can complete this course without one but it will be tougher. Access to, and a beginner's level knowledge of Adobe Creative Suite programs, such as Illustrator, Photoshop and InDesign will help you, especially if you want to complete the optional briefs. Welcome! In this first module I will summarize the assignments and expectations of this course. 4 videos8 readings1 discussion prompt This week we are going to look at how images function in terms of conveying denotative and connotative messages, I'll show you a range of analog and digital imagemaking techniques and discuss how they work. In the first peer review assignment you'll create your own series of images, experimenting with formal techniques. Later, you'll have the opportunity to rework those images to enhance their ability to communicate an idea through connotation in an optional assignment: give it a try, it'll help you develop your communication skills as well as your formal skills! 13 videos2 peer reviews This week we are going to look at typographic terminology and the basic rules for creating typography. I'll show you a range of tips and techniques for working with type, in both a functional and expressive manner, and you'll find out about the process involved in making and controlling typography. This week you'll complete a quiz to make sure you understand the language of typography–this is required. I also highly recommend you complete the two optional peer review assignments. In the first assignment you'll create your own typographic monogram, and you'll use that as a central element in designing a typographic business card in the second assignment. Give them a try, they are the place where you can demonstrate and apply your formal skills, and the place where you get to play with type! 12 videos1 assignment2 peer reviews This week we are going to look at how designers work with shape and color as their fundamental building blocks. You'll learn about visual contrast, color, rhythm and pattern in design. I'll be showing you the process involved in making an abstract design from shapes, and how to use that element to create a repeating pattern design. You'll be completing a quiz (required!) to make sure you understand how visual contrast and color work, and I also highly recommend you complete the two optional peer review assignments. In the first assignment you'll create your own simple and complex design motifs, and you'll use them as the central elements in designing a repeating pattern in the second assignment. The assignments are optional, but they are the place where you get to demonstrate and apply your formal skills, so well worth taking the extra time to complete! 10 videos1 assignment2 peer reviews This week we are going to look at how designers work with visual contrasts, cropping, hierarchy and direction in single images and complex compositions. You'll find out how to control and use scale, weight, direction, texture, and space in a composition, and how to compose work that ranges from the complex to the minimal. In the first peer review assignment you'll create your own abstract compositions that demonstrate your knowledge and control of visual contrast. In the final optional assignment, you can use all your skills from the entire course to create experimental compositions in the form of a poster for a mythical band. This last project is optional, but I strongly suggest you try it out, it'll let you grow and apply your design knowledge and really enjoy and express yourself in your design work! 12 videos1 reading3 peer reviews In this section we've provided some useful resources for students wishing to further their studies in graphic design. The information was authored by Calvin Rye, MFA alumnus of the Graphic Design program at CalArts in consultation with CalArts' Graphic Design faculty and our Office of Admissions. In addition to some advice about selecting the right program of study, we've also included some tips for creating and presenting a strong, organized portfolio and writing your artist statement. These are essential components of any application to a graphic design program, as well as a freelance graphic designer's toolkit. Regardless if you are applying to schools or looking for work in the field, we hope you find these tips and resources useful to your goals. 4 readings

6 modules

Beginner level

https://www.coursera.org/learn/fundamentals-of-graphic-design

98%

Art for Games Specialization

14,736

4.5

Andrew Dennis

Michigan State University

['Design', 'Animation', '3d modeling', 'Video Game Development', 'concept art']

In this beginner focused specialization we will show you the essentials of 2d and 3d game art production as well as concept art for games and current gen game art workflow. While each of the four courses will build your knowledge of the practice of game art, each module is a self contained unit designed to teach a specific area. By the end of the Specialization, you will have a thorough knowledge of the creation of high-quality game art assets. Through these courses, you will be using Maya, Unity, Photoshop, Sketchup, ZBrush, Marmoset Toolbag, and Substance Painter. Applied Learning Project In this specialization learners will create pixel art assets for games, create low-poly 3D assets for games, understand how to study composition, create environment concept painting, create a current gen photo-realistic game prop. Each course within this specialization provides multiple opportunities for students to show their work, and build off what they have done previously. This course is aimed to give you the tools and knowledge you need to start creating simple art for video games made in the Unity game engine. Through the aesthetic of pixel art we will explore artistic principals like shape language, color theory, and composition as well as show you a step by step workflow for creating assets that you can use to make your own games. The course is broken into 4 main modules, props, environments, characters, and animation. Each of these courses will have a series of video lessons alternating between artistic and technical skills culminating in a peer-reviewed project based assignment. The last module will challenge you to take the knowledge learned in the previous 4 and use it to create your own pixel art asset pack. This course is aimed at art novices who are interested in creating art for their own games or contributing to game projects. If you are a game designer or programmer, you will find this course helps give you a glimpse into the world of game art. You will be able to better work with artists, or create your own prototype or final artwork. If you are an artist or visual designer who is interested in bringing your style to the world of video game development, this course will give you the workflow to properly interface with a game engine and help contextualize how your artistic sensibilities can enable gameplay. If you have ever wanted to start making art for video games but have no idea how to start, this course is the perfect for giving you a solid foundation while teaching you usable practical skills. Our goal is to give you a sense of the whole pipeline from creation to setting up in a game engine. This course is aimed to give you the tools and knowledge you need to start creating simple 3D art for video games made in the Unity game engine. Through the aesthetic of pixel art we will explore artistic principals like shape language, color theory, and composition as well as show you a step by step workflow for creating assets that you can use to make your own games. The course is broken into 4 main modules, props, environments, characters, and animation. Each of these courses will have a series of video lessons alternating between artistic and technical skills culminating in a peer-reviewed project based assignment. The last module will challenge you to take the knowledge learned in the previous 4 and use it to create your own pixel art asset pack. This course is aimed at art novices who are interested in creating art for their own games or contributing to game projects. If you are a game designer or programmer, you will find this course helps give you a glimpse into the world of game art. You will be able to better work with artists, or create your own prototype or final artwork. If you are an artist or visual designer who is interested in bringing your style to the world of video game development, this course will give you the workflow to properly interface with a game engine and help contextualize how your artistic sensibilities can enable gameplay. If you have ever wanted to start making art for video games but have no idea how to start, this course is the perfect for giving you a solid foundation while teaching you usable practical skills. Our goal is to give you a sense of the whole pipeline from creation to setting up in a game engine. Model accurate block-in, mid poly meshes Create high poly models with a real world level of accuracy Create game-ready low poly meshes for a real-time environment Texture and render models to give them the appearance of photo-realism In this course we will talk about Concept Art. As a final project we will create a fully finished environment concept, ready for presentation. Throughout the 4 week modules will dive deeply into composition and digital painting techniques to bring your art skills to the next level! So, let's get started!

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/art-for-games

Fundamentals of Project Planning and Management

356,878

4.7

Yael Grushka-Cockayne

University of Virginia

['Project Management', 'Risk Analysis', 'Management', 'Planning', 'Project Planning']

Projects are all around us. Virtually every organization runs projects, either formally or informally. We are engaged in projects at home and at work. Across settings, planning principles and execution methodologies can offer ways in which projects can be run more effectively and efficiently. Project management provides organizations (and individuals) with the language and the frameworks for scoping projects, sequencing activities, utilizing resources, and minimizing risks. This is an introductory course on the key concepts of planning and executing projects. We will identify factors that lead to project success, and learn how to plan, analyze, and manage projects. Learners will be exposed to state-of-the-art methodologies and to considering the challenges of various types of projects. Welcome to the course -- we're excited you're here! In our first week, we'll gain an understanding of what a project is, what it isn't, and why that matters. We'll consider how projects are defined and a project’s three objectives. We'll look at a model for examining a project’s organization and its stakeholders, and then analyze those stakeholders using a power/interest grid. We'll look at the main reasons why many projects fail and then learn how to measure success. Finally, we'll review the key stages in the project life cycle and highlight the important features of each stage. 8 videos4 readings1 assignment3 discussion prompts During our second week, we'll start digging into the details, focusing on how to develop a project plan. We'll understand why we plan and what a plan should or should not include. We'll discuss the process of scoping out a project and see tools that can help us identify what should be included in our project. We'll learn about sequencing project tasks and the nature of the dependencies among project activates. We'll learn how to determine a project’s duration and critical path, how it is determined, and why it is useful. We'll see how we should schedule a project and, finally, we’ll review how you can make changes to a plan to support your overall project objectives. 9 videos1 reading1 assignment1 discussion prompt In our third week, we'll consider the risk and uncertainties projects face. We'll understand what is risky about projects. We'll identify and assess project risks and prioritize these risks in order to focus our attention on those most impactful to the project. We’ll consider schedule risks in detail and ask, "What is the likelihood of finishing on time? What are the drivers that may cause delays in my project?" We'll see how a project budget can be set to include a contingency. Finally, we'll consider situations with a high degree of ambiguity and identify methods than can useful in these situations. 9 videos1 reading1 assignment1 discussion prompt In our final week, we'll move from plan to action and consider the execution phase of a project. We'll learn about the earned value approach for monitoring and controlling progress. We'll consider the individuals who are executing the project and how their habits impact project progress. We'll discuss some alternative methods for project execution such as Agile, Scrum, and Kanban. Finally, we'll review and summarize the course, and our journey from project definition through execution and completion. 9 videos2 readings2 assignments2 discussion prompts

4 modules

Beginner level

https://www.coursera.org/learn/uva-darden-project-management

97%

Business Growth Strategy

40,451

4.7

Michael Lenox

University of Virginia

['Strategic Thinking', 'growth strategy', 'innovation strategy', 'Mergers And Acquisitions (M&A)', 'Business Strategy']

Get the tools you need to analyze, evaluate and recommend specific actions organizations can take to grow their value and avoid common growth pitfalls. In this course, developed at the Darden School of Business at the University of Virginia and taught by top-ranked faculty, you will learn to determine how best to build value, whether by scaling existing markets, entering established markets or creating new markets through innovation and acquisitions. Strategic growth is intentional, proactive, and consistent with a company's purpose. Taking advantage of economies of scale--growing a business by doing more of what it's already doing--is a conceptually easy but operationally complex approach to business growth. In this module, you will learn the Scenario Planning tool to identify and evaluate opportunities to scale an organization. With this tool, you'll have an effective means to understand when and where to grow and how to get there. 12 videos4 readings1 assignment Growth through entry--whether by offering new products in existing markets or offering the same products in new markets--doesn't happen in isolation. Multiple firms compete for these markets and so any discussion of growth through entry has to look at the impact of rivalry. In this module, you'll learn how to apply game theory to analyze, assess, and respond to competitors. With the payoff matrices tool, you'll be able to evaluate options and determine an effective position. 8 videos1 assignment Mergers and acquisitions (M&A) are common--but rarely successful--ways firms attempt to grow their business. In this module, we'll show you the pros and cons of M&A, suggest valid alternatives, and outline effective M&A strategies. Using the Acquisitions Analysis tool, you'll be able to assess the impact of a potential M&A and avoid common pitfalls of this type of growth. 12 videos1 assignment Introducing new ideas, processes, and products that disrupt the market is another common growth strategy. In this module, we'll unlock the keys to innovation, from building an innovative capability to appropriating value from innovation to determining an innovation strategy. Using the Real Options Analysis tool, we'll show you how to grow through innovation and good practices for doing so. The Intel Corporate Venturing case provides an opportunity for you to practice this tool and apply course concepts to a real-world scenario. 11 videos1 reading1 assignment1 peer review

4 modules

10 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/uva-darden-business-growth-strategy

96%

Engaging ELLs and Their Families in the School and Community

3,672

4.6

Claire McLaughlin

Arizona State University

[]

In this course, you will learn how to better and more successfully engage your ELL(s) and their families in the school and community. You will learn how to engage your ELL student in the classroom setting as well as in various aspects of the school including extracurricular activities and the inner workings of the school and education system. You will also be introduced to strategies for engaging the families of your ELL students in the school community and the wider community of your city and state. You will interact with a variety of case studies that highlight teachers, schools, and communities in different cities throughout the United States and the ways in which they successfully engage ELLs and their families. From sharing their experience, you will have the tools necessary to implement strategies and procedures for engaging your ELLs and their families. Upon completing this course, you will be able to: * Define the culture of ELLs in K-12 classrooms across the U.S. * Recognize cultural impact on learning and formal education * Assess your school’s engagement of ELLs and their families * Incorporate culturally sensitive techniques to engage ELLs in the classroom and school * Implement strategies for engaging ELLs’ families in the school and larger community * Design a plan for engagement of ELLs and their families in your school * Create a checklist for school and community resources for engaging ELLs and their families Welcome to week 1 of the course! This is an important module, as it sets the foundation for many of the strategies presented in this course. We hope that you find the module very informative. By the end of this module, you will be able to define the culture of ELLs in K-12 classrooms across the U.S., recognize cultural impact on learning and formal education, assess your school’s engagement of ELLs and their families, incorporate culturally sensitive techniques to engage ELLs in the classroom and school and implement strategies for engaging ELLs’ families in the school and larger community. Let's get started! 9 videos5 readings5 assignments1 discussion prompt Welcome to week 2 of the course! We are thrilled to introduce you to a stellar organization, the American Dream Academy, and the many things that they do to engage families. By the end of this module, you will be able to implement strategies for reaching out to ELL parents, apply concepts of parental training to your own teaching and school contexts, develop a plan for success for parental involvement to implement in your own classroom and school context, apply concepts of teaching training to your own school context, and devise solutions for parent involvement in your own classroom and school context. Let's get started! 10 videos8 readings1 peer review1 discussion prompt Welcome to week 3 of the course! In this module, we showcase another exciting case study in hopes that you can adapt many of the ideas presented. By the end of this module, you will be able to integrate culture into classroom practices such as building background knowledge, implement TPR strategies in classroom activities to support ELL engagement, understand the importance of setting clear expectations for learning and classroom behavior, set clear expectations that are sensitive to cultural differences, use bilingual and multicultural strategies to foster a welcoming environment. Let's get started! 10 videos10 readings1 peer review1 discussion prompt Welcome to week 4 of the course! We are so excited for this module and to introduce you to Alhambra High School. We hope that you find this module inspirational and that you are able to adopt and adapt many of the ideas presented. By the end of this module, you will be able to apply strategies for creating a culturally supportive school environment, connect students to the school community through creating clubs and school-wide activities, implement new strategies for bringing diverse cultures to the school, and use sports as additional opportunities for school engagement. Let's get started! 9 videos7 readings1 peer review1 discussion prompt Welcome to week 5 of the course! In this module, we are going to take you beyond the classroom and look at a variety of ways to engage the family in different aspects of the community. By the end of this module, you will be able to identify organizations in your community that provide support for families, approach organizations regarding working with your students and their families, and implement online resources and apps in your classroom communication as a method for reaching parents and maintaining parent-teacher partnerships. Let's get started! 8 videos6 readings1 peer review1 discussion prompt Welcome to week 6! Congratulations and well done. It is now time to apply the many strategies for Engaging the ELL and their Families in the School and Community to your own teaching context. By the end of this module, you will be able to synthesize course material, complete the final exam and complete the optional peer review. Good luck! 1 video3 readings1 assignment1 peer review

6 modules

19 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/ell-families

The Beauty of Kunqu Opera

8,693

4.8

Prof. Wei Hua 華瑋

The Chinese University of Hong Kong

[]

This course will focus on the historical and cultural background, literary aesthetics, music, and performance of Kunqu, China’s classical opera. After viewing the lecture videos presented by scholars and renowned maestros in the field of Kunqu, students’ understanding and appreciation of Chinese performing arts, classical literature and traditional culture will be enhanced. Welcome to The Beauty of Kunqu Opera! The following lecture videos will give you some ideas of the historical background and characteristics of Kunqu, China’s classical opera that originated more than 600 years ago and blossomed during the late Ming and early Qing dynasties (around 16th – 17th centuries). The introduction is followed by excerpts and analysis of The Peony Pavilion, Kunqu’s masterpiece. The poetic artistry shown in the arias, dialogues and dance movement of the characters exemplifies the aesthetic achievement of Kunqu. 5 videos1 assignment Kunqu means music/song (qu) that originated from the district of Kunshan, Jiangsu province. The word itself shows the fundamental role played by music in this Chinese classical opera. This week, Prof. Lindy Li Mark from the California State University, East Bay will talk about the musical aspect of Kunqu. What are the musical features of Kunqu melodies? What is tune-type and what does a traditional score of Kunqu look like? How is the music of Kunqu different from that of the Western operas? What instruments are used in a Kunqu ensemble? Answers to these questions can be found in the lecture videos. 5 videos1 assignment Just like other genres of Chinese opera, Kunqu has a broad range of role-types, such as male (sheng), female (dan), painted face (jing) and comic (chou). From this week on, legendary performing artists who have devoted their whole lives to Kunqu will talk about the role-types they specialize in and their facial makeup, costume, singing, speaking and movements. In addition, they will demonstrate some of the very important repertoires in Kunqu and share with us the characteristics of each of them. This week, Maestros Yue Meiti and Cai Zhengren will talk about one of the most important role-types of Kunqu, the male role-type. Classical plays such as The Jade Hairpin, The Shepherd, and The Palace of Eternal Life will be introduced as well. 6 videos1 assignment The female role-type is another prominent role-type of Kunqu and can be divided into a number of subtypes. In this week lively lectures and demonstration by Maestros Zhang Jingxian (mature female), Zhang Jiqing (young noble lady), Liang Guyin (vivacious young female) and Wang Zhiquan (martial female) will show us the charisma of the diversified female characters on the Kunqu stage from Chinese classics such as The Lute, The Peony Pavilion and Journey to the West. 9 videos1 assignment The colorful and complex facial makeup of the painted face role-type is probably the most noticeable feature in the eyes of the audience. But what does facial makeup mean and how is it done? This week, Maestro Hou Shaokui will unfold the mysteries for us. He will also share with us his portrayal of Lord Guan, a well-known household character based on the most famous Chinese historical novel Romance of the Three Kingdoms. What is more, this unique character combines the essence of both the painted face and warrior role-types. 5 videos1 assignment When appreciating the well written script and the beautiful melody of Kunqu, sometimes audiences just want a good laugh in the theatre. This cannot be done without the contribution of the comic role-type. This week, Maestro Zhang Mingrong will explain the characteristics of the different subtypes of the comic role-type, namely young chou, fu chou and martial/acrobatic chou. From Maestro Zhang’s demonstration we will also see that mastering the comic role-type requires much more skill than just natural talent. 4 videos1 assignment Drawing examples from the production of The Peony Pavilion (Young Lover’s Edition) and The Jade Hairpin (New Edition), Prof. Kenneth Hsien-yung Pai will illustrate how Kunqu today can attract the younger generation by adding modern elements in stagecraft while preserving the basic aesthetics of Kunqu. 4 videos1 assignment

7 modules

9 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/kunqu-opera

Working for a sustainable future: concepts and approaches

6,887

4.7

Mine Islar

Lund University

['Environmental Policy', 'Sustainability', 'Circular ecomony', 'Scenarios', 'Systems Thinking']

In this course, participants are introduced to key notions and concepts evolving in sustainability science that are relevant to all, independent to one's work or field of interest. After having completed the course, participants will have a better understanding of the vocabulary used today and should demonstrate the ability to reflect critically to integrate different perspectives of environmental, social, and economic sustainability to their specific area of interest or research. Throughout the course, links are made to the Agenda 2030 for Sustainable Development, as our current global road map towards sustainability, and how new approaches and solutions are emerging to describe, understand and address key sustainability challenges. Put simply, the overall aim is to give participants the knowledge and confidence needed to present and discuss ideas with others by applying methods, concepts and the vocabulary exemplified in the course with a more holistic view on the sustainability agenda across topics and disciplines. The course is designed as 5 modules: The first module presents essential concepts within sustainability science, and methods used to describe, frame, and communicate aspects of sustainability. We look at key questions such as what we mean with strong or weak sustainability, resilience, tipping points and the notion of planetary boundaries. We also look at some techniques used of envisioning alternative futures and transitions pathways. The second module is all about systems thinking and how systemic approaches are applied today to achieve long-term sustainability goals. Your will see what we mean with systems thinking and how systems thinking, and design is applied in practice to find new solutions. The third module touches upon drivers for a sustainable future, namely links to economy and business with an introduction to notions of a circular economy, and also policy and regulatory frameworks. We introduce the basics of transformative policy frames and how they are designed and applied through several real-case examples. The fourth module discusses the links between innovation and sustainability, highlighting approaches for technological, social, institutional, and financial innovations. Some examples (or cases) aim to show how different actors across society balance in practice the need for innovative approaches for social, environmental, and economic sustainability. The fifth and last module provides general insights on how we work with models to create various scenarios that help us identify solutions and pathways for a more sustainable world. Three main dimensions are addressed namely climate and climate change, nature and biodiversity, and the importance of data and geodata science to support spatial planning and sustainable land use. This course is brought to you by Lund University with input from four external contributors: - Lund Municipality, Sweden - DigIT Hub, a cluster organisation for digitalisation in society based in Lund, Sweden - Forum for Social Innovation Sweden, a national network across 5 universities - Sustainable Business Hub, a cluster organisation for smart sustainable cities, based in Malmö, Sweden The first module presents essential concepts within sustainability science, and methods used to describe, frame and communicate aspects of sustainability. We look at key questions such as what we mean with strong or weak sustainability, resilience, tipping points and the notion of planetary boundaries. We also look at some techniques used of envisioning alternative futures and transitions pathways. 9 videos9 readings1 assignment3 plugins The second module is all about systems thinking and how systemic approaches are applied today to achieve long-term sustainability goals. Your will see what we mean with systems thinking and how systems thinking and design is applied in practice to find new solutions. 6 videos4 readings1 assignment2 plugins The third module touches upon drivers for a sustainable future, namely links to economy and businesses with an introduction to notions of a circular economy, and also policy and regulatory frameworks. Your will learn the basics of transformative policy frames and how they are designed and applied through a number of real-case examples. 11 videos2 readings1 assignment This module discusses the links between innovation and sustainability, highlighting approaches for technological, social, institutional and financial innovations. Some examples, or cases, aim to show how different actors across society balance in practice the need for innovative approaches for social, environmental and economic sustainability. 9 videos3 readings1 assignment The fifth and last module provides general insights on how we work with models to create various scenarios that help us identify solutions and pathways for a more sustainable world. Three main dimensions are addressed namely climate and climate change, nature and biodiversity, and the importance of data and geodata science to support spatial planning and sustainable landuse. 5 videos3 readings1 assignment

5 modules

Beginner level

18 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/working-for-a-sustainable-future

Algorithmic Thinking (Part 2)

25,467

4.7

Luay Nakhleh

Rice University

['Algorithms', 'Python Programming', 'Algorithmic Efficiency', 'Dynamic Programming']

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems. In part 2 of this course, we will study advanced algorithmic techniques such as divide-and-conquer and dynamic programming. As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Once students have completed this class, they will have both the mathematical and programming skills to analyze, design, and program solutions to a wide range of computational problems. While this class will use Python as its vehicle of choice to practice Algorithmic Thinking, the concepts that you will learn in this class transcend any particular programming language. Sorting, searching, big-O notation, the Master Theorem 13 videos2 readings1 assignment Closest pairs of points, clustering of points, comparison of clustering algorithms 4 readings1 peer review2 app items Dynamic programming, running time of DP algorithms, local and global sequence alignment 7 videos1 assignment Computation of sequence alignments, applications to genomics and text comparison 1 video3 readings1 peer review1 app item

4 modules

Intermediate level

11 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/algorithmic-thinking-2

Mandarin Chinese 1: Chinese for Beginners

83,649

4.8

Wang Jun

Shanghai Jiao Tong University

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Mandarin Chinese 1: Chinese for beginners is a beginner's course of Mandarin Chinese. It uses lectures, short plays, interactive exercises and cultural tips to help learners build a fundamental capability of oral Chinese in real-life situations. At the end of the 5-week course, the learners will reach the following proficiency: ♦ 150 words ♦ 20 language points ♦ handling 5 real-life situations This is a beginners' course, therefore no prerequisite is required. Learning how to greet people; Learning how to introduce one's name and nationality 3 videos4 readings2 assignments1 discussion prompt Learning how to greet people; Learning how to introduce one's name and nationality 2 videos3 readings2 assignments1 discussion prompt Learning how to express numbers; Learning how to express time: the time, years, month and dates 2 videos3 readings2 assignments1 discussion prompt Learning how to express numbers; Learning how to express time: the time, years, month and dates 2 videos3 readings2 assignments1 discussion prompt Learning how to talk about money; Learning the expressions used in shopping 2 videos2 readings2 assignments1 discussion prompt Learning how to talk about money; Learning the expressions used in shopping 2 videos4 readings2 assignments1 discussion prompt Learning how to talk about family, occupations and age. 2 videos2 readings2 assignments1 discussion prompt Learning how to talk about family, occupations and age. 2 videos3 readings2 assignments1 discussion prompt Learning how to order and talk about food. 2 videos2 readings2 assignments1 discussion prompt Learning how to order and talk about food. 3 videos4 readings2 assignments1 peer review1 discussion prompt

10 modules

Beginner level

https://www.coursera.org/learn/mandarin-chinese-1

98%

Find Your Calling: Career Transition Principles for Veterans

Enrollment number not found

Rating not found

Robert Jenkins

Columbia University

['Resume writing', 'Networking', 'interviewing', 'Career transition']

This course provides military veterans with a useful roadmap to transition more smoothly from military service to a new and meaningful civilian career. 12 videos4 readings 10 videos11 readings1 assignment1 discussion prompt 6 videos12 readings1 assignment1 discussion prompt 8 videos11 readings1 assignment2 discussion prompts 7 videos12 readings1 assignment1 discussion prompt 7 videos9 readings1 assignment2 discussion prompts 8 videos9 readings1 assignment 2 videos3 readings 1 reading1 assignment

9 modules

Beginner level

15 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/find-your-calling

AWS Flash - SaaS Technical Fundamentals

Enrollment number not found

Rating not found

AWS Instructor

Amazon Web Services

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Throughout this course, we provide detailed insights and best practices for building and managing SaaS applications on AWS. By the end, you will have a comprehensive understanding of how these elements work together to create a secure, efficient, and scalable SaaS environment. Throughout this course, we will delve deeper into each of these components, providing detailed insights and best practices for building and managing SaaS applications on AWS. By the end, you will have a comprehensive understanding of how these elements work together to create a secure, efficient, and scalable SaaS environment. 1 reading1 assignment

1 module

Beginner level

1 hour to complete

https://www.coursera.org/learn/aws-flash-saas-technical-fundamentals

Fundamental Neuroscience for Neuroimaging

73,616

4.7

Arnold Bakker

Johns Hopkins University

[]

Neuroimaging methods are used with increasing frequency in clinical practice and basic research. Designed for students and professionals, this course will introduce the basic principles of neuroimaging methods as applied to human subjects research and introduce the neuroscience concepts and terminology necessary for a basic understanding of neuroimaging applications. Topics include the history of neuroimaging, an introduction to neuroimaging physics and image formation, as well as an overview of different neuroimaging applications, including functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, perfusion imaging, and positron emission tomography imaging. Each will be reviewed in the context of their specific methods, source of signal, goals, and limitations. The course will also introduce basic neuroscience concepts necessary to understand the implementation of neuroimaging methods, including structural and functional human neuroanatomy, cognitive domains, and experimental design. This week will introduce basic terminology in neuroscience and structural neuroanatomy of the human brain. 5 videos1 assignment4 discussion prompts This week will introduce functional neuroanatomy of the human brain including cognitive domains and neuropsychological assessment of cognition. 5 videos1 assignment5 discussion prompts This week will introduce the principles of neuroimaging and applications in structural and functional neuroimaging. 5 videos1 assignment5 discussion prompts This week will introduce experimental design in functional neuroimaging and special methods in neuroimaging, including functional connectivity MRI, diffusion tensor imaging and spectroscopy imaging. 5 videos1 assignment4 discussion prompts

4 modules

Beginner level

https://www.coursera.org/learn/neuroscience-neuroimaging

96%

Understanding Plants - Part I: What a Plant Knows

113,888

4.8

Professor Daniel Chamovitz, Ph.D.

Tel Aviv University

['Plant Biology', 'Genetics', 'Cell Biology', 'Plant']

For centuries we have collectively marveled at plant diversity and form—from Charles Darwin’s early fascination with stems and flowers to Seymour Krelborn’s distorted doting in Little Shop of Horrors. This course intends to present an intriguing and scientifically valid look at how plants themselves experience the world—from the colors they see to the sensations they feel. Highlighting the latest research in genetics and more, we will delve into the inner lives of plants and draw parallels with the human senses to reveal that we have much more in common with sunflowers and oak trees than we may realize. We’ll learn how plants know up from down, how they know when a neighbor has been infested by a group of hungry beetles, and whether they appreciate the music you’ve been playing for them or if they’re just deaf to the sounds around them. We’ll explore definitions of memory and consciousness as they relate to plants in asking whether we can say that plants might even be aware of their surroundings. This highly interdisciplinary course meshes historical studies with cutting edge modern research and will be relevant to all humans who seek their place in nature. This class has three main goals: 1. To introduce you to basic plant biology by exploring plant senses (sight, smell, hearing, touch, taste, balance). 2. To introduce you to biological research and the scientific method. 3. To get the student to question life in general and what defines us as humans. Once you've taken this course, if you are interested in a more in-depth study of plants, check out my follow-up course, Fundamentals of Plant Biology (https://www.coursera.org/learn/plant-biology/home/welcome). In order to receive academic credit for this course you must successfully pass the academic exam on campus. For information on how to register for the academic exam – https://tauonline.tau.ac.il/registration Additionally, you can apply to certain degrees using the grades you received on the courses. Read more on this here – https://go.tau.ac.il/b.a/mooc-acceptance Teachers interested in teaching this course in their class rooms are invited to explore our Academic High school program here – https://tauonline.tau.ac.il/online-highschool Welcome to "What a Plant Knows (and other things you didn't know about plants)". If you have not already, please review the Course Syllabus for general information about this course. 9 videos1 reading1 assignment1 discussion prompt2 plugins This week we start a systematic review of a plant's sensory systems by starting with plant responses to light. We will cover an overview of human vision, plant responses to light, Darwin's experiments showing plant responses to light, phototropism, phytochrome and flowering, and modern research on phototropism. In other words, this week we get into more advanced concepts in plant sensory biology. The last module is especially advanced, and will be clearer for those of you with a strong biology background. But do not fret, aside from very basic concepts, this module will NOT be included in the exam (you will not be responsible for understanding the intricacies of the experimental methods, etc.). If you have not already, please review the Course Syllabus for general information about this course. 7 videos1 reading1 assignment This week we continue our systematic review of a plant's sensory systems by exploring responses to volatile chemicals (in other words, what a plant smells). We start with an overview of the plant cell, briefly review human olfaction (smell), and then explore how fruits know when to ripen. From there we go over three different experiments that explore plant responses to volatile chemicals and start exploring the controversial question, "Do plants communicate with each other?". 7 videos1 reading1 assignment This week we continue our systematic review of a plant's sensory systems by exploring responses to tactile stimulation (in other words, what a plant feels). We start with an overview of the mechano-sensory system that differentiates between different tactile stimulations, briefly review the way electricity is used in neural communication, and then explore how the Venus flytrap knows when to close, and what powers the opening and closing of the Mimosa leaves. We'll learn how plants change their structure to cope with windy conditions, and go over some of the rather complex biology that is involved in the genetic response in plants to being touched. I'll let you know what I think of the question, Do plants feel pain? And then we'll try to understand whether plants hear, and if they do, which music they prefer. 10 videos1 reading1 assignment1 discussion prompt This week we continue our systematic review of a plant's sensory systems by exploring the 6th sense - proprioception. We start with an overview of the proprioceptive system that allows us to keep our balance and to know where are body parts are in space. Theמ we will explore how plants know up from down, using both experiments from a few hundred years ago, and experiments conducted on the space station. We'll go over the structure of roots more in detail in order to understand where the cells are that sense gravity. We'll revisit phototropism, and learn what the chemical signal is in plants that allows them to respond to light and gravity. And lastly, we'll learn what makes a plant dance. 8 videos1 reading1 assignment This week we move beyond survey of a plant's sensory systems, and explore how plants retain, store and recall sensory information. In other words, we ask the questions, What do plants remember? We'll try to define what we mean by "memory" and briefly review different types of human memory. The we'll look at the short-term memory found in the Venus fly trap, and the long term morphogenic memory first described 50 years ago by the Czech scientist Rudolf Dostal. We'll have a guest lecture from Prof. Nir Ohad about epigenetics and the long-term memory of winter, and even the role of epigenetics in trans-generational memory. 6 videos1 reading1 assignment1 discussion prompt This is the final week in our journey through a plant's sense of the world. This week's lecture has two separate parts. In the first part, we continue last week's discussion of a plant's ability to remember to a more theoretical discussion on the definition of memory and consciousness. This leads us to the question, "Are plants intelligent?". We'll hear what some of the students in this class think of intelligence before finishing with a quick examination of "intelligence", and end with my own take on a plant's, and our place, in the world. In the second part we'll go for a tour of my lab and see our plant growth facilities. I'll give you a brief overview of one of the projects in my lab, and you'll meet a few of the students doing the research. And in the end, you'll even get to meet Dr. Aviva Katz. 6 videos2 readings1 assignment1 plugin

7 modules

Beginner level

https://www.coursera.org/learn/plantknows

96%

Decentralized Finance (DeFi) Infrastructure

46,553

4.8

Cam Harvey

Duke University

['Smart Contract', 'Cryptography', 'governance', 'Decentralized Protocols', 'Blockchain Mechanics']

Decentralized Finance: The Future of Finance is a set of four courses taught by Campbell R. Harvey (Professor of Finance at the Fuqua School of Business, Duke University, and a Research Associate of the National Bureau of Economic Research) that focus on decentralized finance (DeFi). In this first course, we begin by exploring the origins of DeFi and take a broad historical view from the earliest barter economies, such as the first peer-to-peer exchanges of bartering, to present day. The course also looks at historical examples of money having value even though it is not officially backed. We then focus on the key infrastructure components: blockchain, cryptocurrency, smart contracts, oracles, stablecoins and decentralized applications (or dApps). This includes discussion of the mechanics of the Ethereum and Bitcoin blockchains including cryptographic hashing. Next, we focus on the specific problems that DeFi is designed to solve: inefficiency (costly, slow, and insecure today), limited access (1.7 billion are unbanked), opacity (we need to trust regulators to monitor banks and the regulators have mixed records), centralized control (financial system is oligopolistic imposing higher fees than we would have in a competitive market) and lack of interoperability (it is difficult to move funds from one financial institution to another today). The course closes by exploring many of the myths about the crypto space. This module provides a historical perspective of exchange beginning with early barter, specie currency (backed by, e.g., gold), fiat currency and electronic transfers. The module introduces some of the key problems that have arisen with the current system. It closes with the introduction to Satoshi Nakamoto’s famous 2008 paper which introduced cryptocurrency. 6 videos2 readings1 assignment This module introduces the key foundations for DeFi, starting with the mechanics of blockchain including cryptographic hashing. The module then explores the innovation of smart contracting - a key ingredient for DeFi. There is also a discussion of the differences between the first cryptos and stablecoins. 6 videos1 assignment This module explores the key problems with today’s legacy financial system which include: inefficiency (costly, slow, and insecure transactions); limited access (many cannot access banks and many that have bank accounts find it difficult to get loans); opacity (it is unclear how healthy our commercial financial institutions are); centralized control (current system is dominated by oligopolies that push prices higher than competitive prices) and interoperability (difficulty in moving funds across different legacy financial institutions). 5 videos1 assignment The final module explores various different myths including: all cryptocurrencies are anonymous; blockchains are routinely hacked; quantum computing will destroy all blockchain based currencies; and the crypto ecosystem is so small that it is unlikely to compete with legacy financial institutions. 2 videos1 assignment

4 modules

Beginner level

https://www.coursera.org/learn/decentralized-finance-infrastructure-duke

97%

Learning How To Learn for Youth

88,534

4.8

Dr. Barbara Oakley

Arizona State University

['Test Preparation', 'Learning To Learn', 'Pomodoro Technique', 'Meta Learning']

Based on one of the most popular open online courses in the world, this course gives you easy access to the learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. No matter what your current skill level, using these approaches can help you master new topics, change your thinking and improve your life. This course explains: * Why sometimes letting your mind wander is an important part of the learning process * How to avoid "rut think" in order to think outside the box * The value of metaphors in developing understanding * A simple, yet powerful, way to stop procrastinating If you’re already an expert, these strategies will turbocharge your learning, including test-taking tips and insights that will help you make the best use of your time on homework and problem sets. We all have the tools to learn what might not seem to come naturally to us at first—the secret is to understand how the brain works so we can unlock its power. Filled with animations, application questions, and exercises, this course makes learning easy and fun! In this module, we'll use metaphor and analogy to help you more easily understand key ideas about how your brain works. You will discover two modes of thinking—you can use these modes in different ways to improve your learning. We will also show you a powerful tool for tackling procrastination, give you some great memory tips, and point out why "sleeping on it" can be a good idea! 5 videos1 reading1 assignment1 discussion prompt4 plugins In this module, we explore the brain’s process for storing information in long-term memory in an easy to understand metaphor involving a school bag, a locker and an octopus. Then, we will talk about some of the best ways to access your brain’s most powerful long-term memory systems, like metaphor, recall, memory palace and rhyming. 6 videos2 readings1 assignment2 discussion prompts In this module, we’re going to talk more about important ideas and techniques that will enhance your ability to learn. You’ll also discover how to avoid “information overload,” and how to recognize your own strengths. Fighter pilots and surgeons use checklists to help them with their critical duties—you can use a similar checklist to help you prepare for tests. Ultimately, you will learn more about the joys of living a life filled with learning! 6 videos5 readings2 assignments2 discussion prompts3 plugins

3 modules

Beginner level

https://www.coursera.org/learn/learning-how-to-learn-youth

98%

International Business I

66,291

4.7

Doug E Thomas, Ph.D.

University of New Mexico

['Environmental Economics', 'Global Marketing', 'Trading', 'Market (Economics)']

We live in a world of intensifying global relationships, one in which international business has become the key determinant of economic development and prosperity. This course, Global Business Environment, Part I, introduces students to a fundamental understanding of the socioeconomic political, cultural, and linguistic environment in which international businesses operate. This course utilizes an inquiry-based approach to understanding country level relationships in the Global Business Environment. It surveys the global business environment by asking and answering key questions about society, the global economy, cultures, institutions and languages. The questions we will ask are: 1. What is Globalization?, 2. Is Globalization New?, 3. How do Political and Social Institutions impact National Economic Development?, 4. What is the role of Culture?, 5. What are the Gains from Trade?6. Free Trade, Free-r Trade or Managed Trade?, 7. What are Foreign Currencies and how are Exchange Rates Determined?, 8. What does the Current Global Business Environment look like? This inquiry-based approach creates reflective opportunities for students to better understand the environment in which businesses operate. Lectures are delivered in an engaging manner, which encourages reflection and inquiry. What is Globalization? 6 videos1 assignment Is Globalization New? 7 videos1 assignment How do Political and Social Institutions impact National Economic Development? 8 videos1 assignment What is the role of Culture? 6 videos1 assignment What are the Gains from Trade? 6 videos1 assignment Free Trade, Free-r Trade or Managed Trade? 7 videos1 assignment

6 modules

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/international-business

98%

Generative Deep Learning with TensorFlow

20,947

4.9

Laurence Moroney

DeepLearning.AI

['Variational AutoEncoders', 'Auto Encoders', 'Generative Adversarial Networks', 'Neural Style Transfer']

In this course, you will: a) Learn neural style transfer using transfer learning: extract the content of an image (eg. swan), and the style of a painting (eg. cubist or impressionist), and combine the content and style into a new image. b) Build simple AutoEncoders on the familiar MNIST dataset, and more complex deep and convolutional architectures on the Fashion MNIST dataset, understand the difference in results of the DNN and CNN AutoEncoder models, identify ways to de-noise noisy images, and build a CNN AutoEncoder using TensorFlow to output a clean image from a noisy one. c) Explore Variational AutoEncoders (VAEs) to generate entirely new data, and generate anime faces to compare them against reference images. d) Learn about GANs; their invention, properties, architecture, and how they vary from VAEs, understand the function of the generator and the discriminator within the model, the concept of 2 training phases and the role of introduced noise, and build your own GAN that can generate faces. The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture, and gives them the tools to create and train advanced ML models. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models. This week, you will learn how to extract the content of an image (such as a swan), and the style of a painting (such as cubist, or impressionist), and combine the content and style into a new image. This is called neural style transfer, and you'll learn how to extract these kinds of features using transfer learning. 13 videos7 readings1 assignment1 programming assignment3 ungraded labs This week, you’ll get an overview of AutoEncoders and how to build them with TensorFlow. You'll learn how to build a simple AutoEncoder on the familiar MNIST dataset, before diving into more complicated deep and convolutional architectures that you'll build on the Fashion MNIST dataset. You'll get to see the difference in results of the DNN and CNN AutoEncoder models, and then identify ways to denoise noisy images. You'll finish the week building a CNN AutoEncoder using TensorFlow to output a clean image from a noisy one! 6 videos1 reading1 assignment1 programming assignment5 ungraded labs This week you will explore Variational AutoEncoders (VAEs) to generate entirely new data. In this week’s assignment, you will generate anime faces and compare them against reference images. 6 videos3 readings1 assignment1 programming assignment1 ungraded lab This week, you’ll learn about GANs. You'll learn what they are, who invented them, their architecture and how they vary from VAEs. You'll get to see the function of the generator and the discriminator within the model, and the concept of 2 training phases and the role of introduced noise. Then you'll end the week building your own GAN that can generate faces! How cool is that! 7 videos10 readings1 assignment1 programming assignment3 ungraded labs

4 modules

Intermediate level

https://www.coursera.org/learn/generative-deep-learning-with-tensorflow

95%

Single Page Web Applications with AngularJS

125,439

4.9

Yaakov Chaikin

Johns Hopkins University

['Unit Testing', 'Web Development', 'JavaScript', 'Angularjs']

Do you want to write powerful, maintainable, and testable front end applications faster and with less code? Then consider joining this course to gain skills in one of the most popular Single Page Application (SPA) frameworks today, AngularJS. Developed and backed by Google, AngularJS is a very marketable skill to acquire. In this course, we will explore the core design of AngularJS 1.x (latest version of AngularJS 1), its components and code organization techniques. We will enhance the functionality of our web app by utilizing dependency injection to reuse existing services as well as write our own. We will create reusable HTML components that take advantage of AngularJS data binding as well as extend HTML syntax with a very powerful feature of AngularJS called directives. We’ll set up routing so our SPA can have multiple views. We will also learn how to unit test our functionality. At the end of this course, you will build a fully functional, well organized and tested web application using AngularJS and deploy it to the cloud. In this module, we are going to start by going over how grading works for this course, will introduce some recommended books, as well as give you the information on how to find all of the source code that you will see throughout the course. We will then dive into the development environment setup for both Mac and Windows. The core of this module will be the introduction not only to the basics of AngularJS, but more importantly, the concepts that back AngularJS as a good solution for developing front-end web applications. To become a good software developer and not just with AngularJS, you will need to understand these concepts. But for becoming a good AngularJS developer, these concepts are essential, because they will allow you to understand the issues the framework is addressing and therefore get a good grasp on the solutions AngularJS is offering. 21 videos7 readings9 assignments1 peer review We will start this module by learning how to use Angular filters to manipulate our data into the format we want and learn how to create our own custom filters. We will then dive deep into the digest cycle, which is the process AngularJS uses to magically update our web page with the bound data from our ViewModel or the controller. Understanding this process is crucial in getting comfortable with AngularJS. We'll also see some cases where we'll need to assist that process somewhat and understand why that is. After that, we'll learn one of the most fundamental concepts in the Javascript programming language, which is Prototypal Inheritance. Clear understanding of that topic is a must before we talk about inheritance between AngularJS controllers in our application. We'll finish off the module by learning how to create our own custom Angular services as well as how to configure them. With custom Angular services we'll be able to share data across different controllers or other components in our application. We will also learn a few useful Angular directives that allow us to place looping and conditional logic direction into our HTML. You'll see that by the end of this module, you'll have the skills to create a fairly sophisticated web application that starts to use some of the more advanced software architecture techniques. 25 videos3 readings12 assignments1 peer review Welcome to module 3! In this module, we go over a lot of essential features of AngularJS. We will start with learning about the Promise API. While Promises are essential to Angular, this topic reaches far beyond Angular. It's really an essential topic to understanding modern web development with Javascript. We will also learn about making calls to the server through the built in Angular service called the HTTP service. We'll finish off the module by spending a considerable amount of time on THE crown feature of AngularJS: directives. Directives are really at the core of the entire framework. They not only allow us to extend the functionality of existing HTML elements, which is already pretty amazing in an of itself, but they also allow us to create our own element with custom view and custom behavior. Pretty exciting stuff! 19 videos3 readings10 assignments1 peer review In this module, we start by introducing the idea of Component-based architecture. We will then delve into the AngularJS component API. The component API is something that was just recently added into Angular 1 and it's not only supposed to improve your application through the use of Component-based architecture, but also prepare you for an upgrade to Angular version 2, which uses components almost exclusively. We will then learn about the AngularJS event system and how to split up our application into smaller modules that can then be glued together to produce our final application. We'll finish off the module by diving fairly deep into Routing between views in your application and, specifically, into the use of the ui-router module, which is one of the most popular open source routing solutions within the AngularJS ecosystem. In fact, it's so popular that even the main Google documentation for routing in Angular links to ui-router. Routing is a very important topic. Without it, your Single Page Application is stuck displaying just 1 view, without an elegant way to display other views. 22 videos3 readings9 assignments1 peer review Welcome to module 5! This is the last module in the course. We'll start this module by learning just how easy it is to validate forms with Angular. We will then delve into unit testing our AngularJS code. We will go over how to set up tests for every type of major Angular artifact: controller, service, directive, and component, as well as how to test services that access the network through the HTTP service. However, the last part of the module is the most fun. We will take the site that was developed for our real client in my previous course and re-write the entire thing using AngularJS. However, the coding fun doesn't have to stop there. After you finish the required part of the course, you can move on to the optional bonus part where we take our newly developed AngularJS application and enhance with it even more features that will allow the restaurant owners to administer their own data. We'll go over setting up authentication, editing restaurant menu items, uploading menu item pictures and so on. 32 videos6 readings7 assignments1 peer review

5 modules

Intermediate level

https://www.coursera.org/learn/single-page-web-apps-with-angularjs

97%

Family Spirit Nurture

Enrollment number not found

Rating not found

Sarah Vanegas, MS

Johns Hopkins University

['Responsive Feeding for Infants', 'Motivational Interviewing for nutrition', 'Basic nutrition knowledge', 'Breastfeeding promotion', 'Connecting to Indigenous foods and Native foodways']

This course is designed for health educators and home visitors serving families with infants 0-6 months old. Learners will gain knowledge and skills to make a positive impact on healthy infant nutrition and growth as well as maternal and family nutrition. This course is uniquely tailored towards Indigenous families and approaches nutrition through a strengths-based lens connecting to Indigenous foods and Native Foodways. How can health educators have meaningful discussions with families around nutrition and healthy eating? A careful approach that connects families to strengths and culture can open the door for success. We explore a strengths-based approach, connecting to Native Foodways and Indigenous foods, and four brief techniques of motivational interviewing specific to promoting healthy nutrition choices. 5 videos6 readings1 assignment1 discussion prompt1 plugin Everything a health educator needs to know about nutrients, food groups, and making sense out of nutrition facts labels. Also, the importance of moderating sugar intake and answers to some commonly asked questions around sugary drinks. 7 videos4 readings2 assignments Why the first few months of baby's life are critical for establishing healthy feeding patterns. How to tell if a baby is hungry or full? Why breastfeeding is about more than just providing great nutrition. Tips and tricks on starting solid foods when baby shows readiness around 6 months and what caregivers can do to set a powerful healthy eating example (teaching their child to love healthy food and drinks). 6 videos4 readings3 assignments2 plugins Understanding a baby's unique personality traits can help parenting go as smoothly as possible. How can we understand and work with each baby's feeding style? Also, we'll explore caregiver mental health and coping with challenges of parenting. 1 video3 readings1 assignment1 discussion prompt

4 modules

Beginner level

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/family-spirit-nurture

Managing Asthma, Allergies, Diabetes, and Seizures in School

20,943

4.8

Daniel Nicklas

University of Colorado System

[]

Welcome to School Health specialization: Managing Asthma, Anaphylaxis, Food Allergies, Diabetes, and Seizures in School course. In this course, you will learn about these common medical issues students face and how to best support students who suffer from them. We will also take a holistic look at how we can best support overall student health. We will take a look at how the school nurse provides support to students and staff in each scenario and how to plan ahead in the event of an emergency. We will walk through the reasons that schools should promote student health and how we can support students that face these common medical conditions As part of the course, we will introduce two students to help all of this information come alive. Prepare yourself to learn about these common medical conditions. Let’s get started! In the following module you will learn more about the obstacles students with asthma face and how to be prepared to assist students with asthma and help them manage their symptoms. While our abilities to manage asthma have improved over the years, we still face many challenges. We will learn more about the staff-related responsibilities in aiding a student with asthma and how to compose a plan in the event of an emergency. You will learn how to recognize asthma triggers and how to administer proper therapies while supporting the social emotional needs of the student. 10 videos9 readings2 assignments In this module you will learn about Type 1 Diabetes and how best to assist students with Type 1 Diabetes. Included in the lessons are an overview of Type 1 Diabetes as a condition, how to create plans in the event of an emergency, an overview of relevant federal regulations, the role of the school nurse as a resource, and supporting the social emotional needs of students with Type 1 Diabetes. 5 videos5 readings1 assignment Next we’ll learn about seizures and how to assist students who suffer from seizures. Seizures can be a scary thing. In the following lessons you’ll learn what seizures are, what causes them, why epilepsy is often associated with seizures, signs and symptoms to look for, information on seizure first aid, the role of the school nurse as a resource, and how to best support students who experience a seizure. 6 videos6 readings1 assignment There are a wide variety of allergies represented in a given school population. In this module we’ll learn more about allergies and their effects and the role of the immune system. Once we’ve covered the basics we’ll dive into reactions ranging from mild to severe and anaphylaxis, recognizing symptoms, helping students manage their allergies at school, medications used in the event a student is exposed to an allergen, how to plan for emergencies, and how to minimize exposure. 7 videos6 readings1 assignment

4 modules

Beginner level

https://www.coursera.org/learn/managing-asthma-allergies-diabetes-and-seizures-in-school

98%

Advanced Understanding of Stocks and Bonds

5,158

4.6

Gautam Kaul

University of Michigan

['Bond Valuation', 'Trading in finacial market', 'Stock Valuation']

This final course will cover more advanced aspects of bonds and stocks that will help you make smart personal decisions and develop a keen understanding of how governments and companies borrow from us. You will better understand stocks and bonds valuation and take a deeper dive using real-world problems. For stocks, you will review what you have already learned and understand valuation. You will learn about growth, different types of growth both bad and good. You will also get an opportunity to apply these concepts in practice assignments. For bonds: you will review what you have already learned. You will learn about different sources of risk in bonds. Lastly you will get an opportunity to apply these concepts in practice assignments. After completing this course, you will have a deeper understanding of how bonds and stocks are valued and the risks involved in both. You will be able to apply this knowledge to understand the workings of a company and how it creates value. This will enable you to invest with more confidence and also bring a special and critical lens to a company’s decisions. This course is part of the four-course Foundational Finance for Strategic Decision Making Specialization. This course follows the same pattern as the second course did relative to the first. In Course 3 we covered the basics of bonds and stocks with simpler applications. In this course, we will delve deeper into bond and stocks with an emphasis on applications. In the first two weeks we will be focused on bonds. Also the Practice and Graded Assignments in weeks 2 and 4 are deliberately structured to contain ten questions, with some overlap with Course 3 followed by increasing complexity. 3 videos3 readings This week is all about practicing applications and attempting the Graded Assignment. I would encourage you to also revisit Yahoo Finance and review the data on bonds and read articles on bond markets. 2 readings2 assignments This module is probably the most interesting module in this Specialization because it shows you how any idea adds value by relating it to the price of a stock. You will gain a deep understanding of how firms create value and how growth may not be a good policy. All the concepts are introduced using applications. This module conveys the essence of value creation. You are encouraged to start Practicing the assignments. 4 videos2 readings This week is again devoted entirely to financial analysis and assignments. Each assignment has ten questions and some are quite complex. You must take this opportunity to learn finance. All the skills you develop will help you both personally and professionally. The beauty of finance is that the frameworks are the same regardless of whether you are making a personal or a professional decision. 1 reading2 assignments

4 modules

Intermediate level

12 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/bonds-and-stocks-two

Data Understanding and Visualization

Enrollment number not found

Rating not found

Di Wu

University of Colorado Boulder

['Seaborn', 'Python Programming', 'Pandas', 'Data Visualization', 'Matplotlib']

The "Data Understanding and Visualization" course provides students with essential statistical concepts to comprehend and analyze datasets effectively. Participants will learn about central tendency, variation, location, correlation, and other fundamental statistical measures. Additionally, the course introduces data visualization techniques using Pandas, Matplotlib, and Seaborn packages, enabling students to present data visually with appropriate plots for accurate and efficient communication. Learning Objectives: 1. Understand and communicate the various aspects of statistics of datasets, including measures of central tendency, variation, location, and correlation. 2. Gain insights into basic statistical concepts and use them to describe dataset characteristics effectively. 3. Utilize Pandas for data manipulation and preparation to set the foundation for data visualization. 4. Master the utilization of Matplotlib and Seaborn to create accurate and meaningful data visualizations. 5. Choose appropriate plot types for different data types and research questions to enhance data comprehension and communication. Throughout the course, students will actively engage in practical exercises and projects, enabling them to explore statistical concepts, conduct data analysis, and effectively communicate insights through compelling visualizations. Throughout the course, students will actively engage in practical exercises and projects that involve statistical analysis and data visualization. By the end of the course, participants will be equipped with the knowledge and skills to explore, analyze, and communicate insights from datasets effectively through descriptive statistics and compelling visualizations. The "Data Statistics" week provides students with a fundamental understanding of statistics as it relates to data analysis. You will explore essential statistical concepts, including measures of central tendency, variation, location, correlation, and other key statistical measures. This week serves as a crucial foundation for students to develop your data analysis and interpretation skills. 1 video4 readings1 assignment1 discussion prompt The "Data Visualization with Pandas" week focuses on uilizing the Pandas package to create effective and insightful data visualizations. You will learn various data visualization techniques to present and communicate data in a clear and concise manner, enhancing your ability to derive valuable insights from datasets. 1 video2 readings1 assignment1 discussion prompt The "Data Visualization with Matplotlib" week focuses utilizing the Matplotlib package to create visually appealing and informative data visualizations. You will learn various data visualization techniques to effectively present and communicate data insights, enabling you to derive valuable information from datasets. 1 video2 readings1 assignment1 discussion prompt The "Data Visualization with Seaborn" week focuses on utilizing the Seaborn package to create sophisticated and visually appealing data visualizations. You will learn various data visualization techniques using Seaborn to effectively present and communicate complex data patterns and relationships, empowering you to gain valuable insights from datasets. 1 video2 readings2 assignments1 discussion prompt

4 modules

Intermediate level

25 hours to complete (3 weeks at 8 hours a week)

https://www.coursera.org/learn/data-understanding-and-visualization

Excel to MySQL: Analytic Techniques for Business Specialization

222,881

4.6

Jana Schaich Borg

Duke University

['Business Communication', 'Big Data', 'Binary Classification', 'Data Analysis', 'Microsoft Excel', 'Business Analysis', 'SQL', 'Business Analytics', 'Tableau Software', 'Data Visualization', 'MySQL']

In this Specialization, you’ll learn to frame business challenges as data questions. You’ll use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights. In the final Capstone Project, you’ll apply your skills to explore and justify improvements to a real-world business process. The Capstone Project focuses on optimizing revenues from residential property, and Airbnb, our Capstone’s official Sponsor, provided input on the project design. Airbnb is the world’s largest marketplace connecting property-owner hosts with travelers to facilitate short-term rental transactions. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies. Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality. This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model. The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression. All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become fluent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1). The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classification (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel. One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles. This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself! By the end of this course, you will have a clear understanding of how relational databases work, and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world. In this final course you will complete a Capstone Project using data analysis to recommend a method for improving profits for your company, Watershed Property Management, Inc. Watershed is responsible for managing thousands of residential rental properties throughout the United States. Your job is to persuade Watershed’s management team to pursue a new strategy for managing its properties that will increase their profits. To do this, you will: (1) Elicit information about important variables relevant to your analysis; (2) Draw upon your new MySQL database skills to extract relevant data from a real estate database; (3) Implement data analysis in Excel to identify the best opportunities for Watershed to increase revenue and maximize profits, while managing any new risks; (4) Create a Tableau dashboard to show Watershed executives the results of a sensitivity analysis; and (5) Articulate a significant and innovative business process change for Watershed based on your data analysis, that you will recommend to company executives. Airbnb, our Capstone’s official Sponsor, provided input on the project design. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. "Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone."

5 course series

Beginner level

6 months (at 5 hours a week)

https://www.coursera.org/specializations/excel-mysql

Low Intermediate English: Technology

1,829

4.4

Rebecca Payne-Passmore

Voxy

['English Grammar', 'Reading Comprehension', 'Business English', 'Listening Comprehension', 'English Vocabulary']

Living in the digital age means not only having a lot of technology, but talking about it a lot too. In this course, we’re going to focus on the technology and devices that we use in our daily lives. Learning activities in this course will take place on Voxy, an engaging language learning platform that automatically adapts to your current level and your performance across reading, listening, speaking, grammar, and vocabulary skills so that every lesson is optimized for rapid improvement. Each week is made up of engaging, short, task-based lessons that can be done anywhere, anytime. Lessons include content from the real world, so you will learn from real conversations and emails between friends and colleagues exchanging information and assistance. By the end of the course, you should feel pretty comfortable discussing technology with friends and colleagues alike! This week, you will learn about this course and understand how to use Voxy's innovative platform. 4 videos4 readings2 assignments2 app items This week, you will learn how to talk about the devices, social media, and apps that you use in your daily life, as well as their pros and cons. 1 video4 readings4 app items1 discussion prompt This week, you will learn how to talk about how technology is changing, and the impact it has on the world we live in. 1 video4 readings4 app items1 discussion prompt This week, you will listen to people giving advice on how to use technology to keep your data safe at work, to work from home, and to stay healthy. 1 video3 readings1 assignment3 app items This week, you will learn language to use when asking coworkers and IT professionals for help with tech issues. 1 video3 readings3 app items1 discussion prompt 3 videos4 readings1 assignment2 app items1 discussion prompt

6 modules

19 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/low-intermediate-english-technology

Convolutional Neural Networks

521,051

4.9

Andrew Ng

DeepLearning.AI

['Facial Recognition System', 'Tensorflow', 'Convolutional Neural Network', 'Deep Learning', 'Object Detection and Segmentation']

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI. Implement the foundational layers of CNNs (pooling, convolutions) and stack them properly in a deep network to solve multi-class image classification problems. 12 videos6 readings1 assignment2 programming assignments Discover some powerful practical tricks and methods used in deep CNNs, straight from the research papers, then apply transfer learning to your own deep CNN. 14 videos3 readings1 assignment2 programming assignments Apply your new knowledge of CNNs to one of the hottest (and most challenging!) fields in computer vision: object detection. 14 videos4 readings1 assignment2 programming assignments Explore how CNNs can be applied to multiple fields, including art generation and face recognition, then implement your own algorithm to generate art and recognize faces! 11 videos6 readings1 assignment2 programming assignments

4 modules

Intermediate level

https://www.coursera.org/learn/convolutional-neural-networks

95%

Microsoft Copilot for Security

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Security Operations Management', 'Strategic Security Planning', 'Advanced AI Integration', 'Prompt Engineering', 'Custom Security Solutions Development']

Did you know that integrating AI with cybersecurity can reduce incident response times by up to 70%? This Short Course was created to help cybersecurity professionals harness the power of Microsoft Security Copilot to enhance their security strategies. By completing this course you'll be able to integrate advanced AI capabilities into your security operations, enabling faster and more effective responses to threats. More specifically, in this 3-hour-long commitment, you will learn how to understand the functionalities of Microsoft Security Copilot, integrate it with various security tools, and apply its capabilities in practical security scenarios. This project is unique because it bridges the gap between AI technology and practical security needs. To be successful in this project, you will need at least 2 years of experience in cloud security, 1 year with Microsoft security products like Sentinel and Defender XDR, and foundational knowledge of KQL. By the end of this lesson, you will become familiar with the course objectives, syllabus and will have met the instructor. 1 video1 reading By the end of this lesson, you will understand the various Microsoft Copilots available within the Microsoft Suite and how they function as generative AI assistants integrated into these applications. You will learn how these Copilots deliver solutions in natural language and explore their roles and functionalities as key tools for synthesizing information and providing actionable insights in Microsoft applications like Edge, Word, and Excel. 4 videos1 reading1 assignment By the end of this lesson, learners will be able to describe how Microsoft Copilot for Security functions and demonstrate how to effectively integrate it with other security tools. Additionally, learners will be able to demonstrate provisioning Microsoft Copilot for Security as a solution to their individual security infrastructure needs. 3 videos2 readings1 assignment By the end of this lesson, learners will have reviewed Microsoft Copilot for Security's embedded and standalone capabilities across various Microsoft Security products. 5 videos1 assignment By the end of this lesson, learners will be able to craft effective prompts using best practices in prompt engineering, recognize use cases for utilizing built-in promptbooks, and develop their own custom promptbooks. 3 videos1 reading2 assignments

5 modules

Intermediate level

3 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/microsoft-copilot-for-security

Six Sigma Principles

Enrollment number not found

Rating not found

David Cook, PhD

Kennesaw State University

[]

This course is for you if you are looking to learn more about Six Sigma or refresh your knowledge of the basic components of Six Sigma and Lean. Six Sigma skills are widely sought by employers both nationally and internationally. These skills have been proven to help improve business processes and performance. This course will introduce you to the purpose of Six Sigma and its value to an organization. You will learn about the basic principles of Six Sigma and Lean. Your instructors will introduce you to, and have you apply, some of the tools and metrics that are critical components of Six Sigma. This course will provide you with the basic knowledge of the principles, roles, and responsibilities of Six Sigma and Lean. Every module will include readings, videos, and a quiz to help make sure you understand the material and concepts that are studied. You will also have the opportunity to participate in discussions and peer review exercises to give you the opportunity to apply the material to your daily life. Our applied curriculum is built around the latest handbook The Certified Six Sigma Handbook (2nd edition) and students will develop /learn the fundamentals of Six Sigma. Registration includes online access to course content, projects, and resources but does not include the companion text The Certified Six Sigma Handbook (2nd edition). The companion text is not required to complete the assignments. However, the text is a recognized handbook used by professionals in the field. Also, it is a highly recommended text for those wishing to move forward in Six Sigma and eventually gain certification from professional agencies such as American Society for Quality (ASQ). Welcome to the Six Sigma Yellow Belt Specialization! Six Sigma skills are widely sought by employers both nationally and internationally. These skills help to improve business processes and performance. Your team of instructors, Dr. Bill Bailey, Dr. David Cook, Dr. Christine Scherrer, and Dr. Gregory Wiles, currently work in the College of Engineering and Engineering Technology at Kennesaw State University. They have collaborated to create a specialization that is all encompassing of the Six Sigma methodologies for both Yellow and Green belt. Completion of this specialization will provide you with the knowledge to either continue to full Six Sigma certification or simply advance your knowledge professionally. In this module you will be introduced to the foundations of Six Sigma, the purpose of lean, and the value to the organization as a whole. 11 videos1 reading4 assignments In this module Dr. Bill Bailey will introduce you to the different types of quality tools as well as important Six Sigma metrics that can be used throughout the DMAIC process. Quality tools and metrics are a critical tool for process improvement. This module will introduce you to some of the most common quality tools as well as the most important Six Sigma metrics. 10 videos1 assignment2 peer reviews Teamwork is an essential component of successful quality improvement work. Many successful organizations have leaders who work in teams. In this module you will learn about why teams are so important to the Six Sigma process, the different types of teams and their different objectives, the different stages of team development, decision making methods for use in teams, and team communication methods. 6 videos2 assignments1 discussion prompt In this module you will be introduced to the purpose of lean and its methodologies. You will learn about the value of lean to an organization. This module will build off of what you have learned in the previous modules and help you to better understand how to better serve customers. 8 videos2 assignments1 discussion prompt

4 modules

Beginner level

9 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/six-sigma-principles2

Windows OS Forensics

5,652

4.7

Denise Duffy

Infosec

['forensics', 'windows os', 'Data Recovery']

The Windows OS Forensics course covers windows file systems, Fat32, ExFat, and NTFS. You will learn how these systems store data, what happens when a file gets written to disc, what happens when a file gets deleted from disc, and how to recover deleted files. You will also learn how to correctly interpret the information in the file system data structures, giving the student a better understanding of how these file systems work. This knowledge will enable you to validate the information from multiple forensic tools properly. This module explains the various numbering schemas used throughout computer forensics. In this module, you'll explore the numbering schemas used in computer forensics. This knowledge allows the student to interpret data at the hex and binary levels. This skill is necessary to validate forensic software tools and gives the student an understanding of where to locate the data displayed by their forensic software. This information is notably beneficial for court proceedings. 4 videos A look at the master boot record and the GUID partition table. This module demonstrates the difference between the master boot record and the GUID partition table. This information gives the student an understanding of where to locate both partitions and data on the drive. The forensic student learns how to interpret the master boot record and locate the volume boot record for each volume on the drive. 6 videos This module explores the structure of the FAT file system. This module covers the structure and layout of the FAT file system. The student develops an understanding of how the FAT file system writes a file to a drive and deletes a file from a drive. With this knowledge, the examiner can recover deleted data or recover data from a reformatted drive. 6 videos In this module, you'll explore the details of the NTSF file system. NTSF is a crucial component of forensic examinations. This module explains how the file system organizes information and where data is located on the drive. It also covers where the metadata for the file is stored and the changes that occur at a file system level when someone deletes or creates a file. 6 videos Take a closer look at the details of the ex-FAT file system. In this module, the student learns the structure and layout of the ex-FAT file system, how the file system tracks files, where it stores the file metadata and how to recover deleted data. 5 videos Explore the complexities and challenges of Windows Registry forensics. This module covers the history and function of the Registry. It includes how to examine the live Registry, the location of the Registry files on the forensic image and how to extract files. After examining the files with forensic tools, the student can locate relevant artifacts such as USB device connection times, recently used documents, program last run times and programs set to run at startup. 4 videos1 assignment

6 modules

Intermediate level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/windows-os-forensics

Differential Equations Part III Systems of Equations

Enrollment number not found

Rating not found

Kil Hyun Kwon

Korea Advanced Institute of Science and Technology(KAIST)

[]

This introductory courses on (Ordinary) Differential Equations are mainly for the people, who need differential equations mostly for the practical use in their own fields. So we try to provide basic terminologies, concepts, and methods of solving various types of differential equations as well as a rudimentary but indispensable knowledge of the underlying theory and some related applications. The prerequisites of the courses is one- or two- semester calculus course and some exposure to the elementary theory of matrices like determinants, Cramer’s Rule for solving linear systems of equations, eigenvalues and eigenvectors. Table of Contents Differential Equations Part I Basic Theory Chapter 1 Introduction Chapter 2 First Order Differential Equations Chapter 3 Mathematical Modelling and Applications Chapter 4 Linear Second Order Equations Chapter 5 Applications of Second Order Equations Differential Equations Part II Series Solutions Chapter 1 Euler Equations Chapter 2 Series Solutions of Linear Equations Chapter 3 Special Functions: Bessel Functions and Legendre Polynomials Differential Equations Part III Systems of Differential Equations Chapter 1 Systems of Linear Equations Chapter 2 Stability of Autonomous Systems 6 videos 7 videos1 assignment 6 videos1 reading1 assignment 5 videos 5 videos 5 videos1 reading1 assignment

6 modules

Intermediate level

10 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/differential-equations-part-iii-systems-of-equations

Google Cloud Big Data and Machine Learning Fundamentals

322,639

4.7

Google Cloud Training

Google Cloud

['Tensorflow', 'Bigquery', 'Google Cloud Platform', 'Cloud Computing']

This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud. This section welcomes learners to the Big Data and Machine Learning Fundamentals course, and provides an overview of the course structure and goals. 2 videos This section explores the key components of Google Cloud's infrastructure. It's here that we introduce many of the big data and machine learning products and services that support the data-to AI lifecycle on Google Cloud. 10 videos1 reading1 assignment1 app item This section introduces Google Cloud's solution to managing streaming data. It examines an end-to-end pipeline, including data ingestion with Pub/Sub, data processing with Dataflow, and data visualization with Looker and Looker Studio. 9 videos1 reading1 assignment1 app item This section introduces learners to BigQuery, Google's fully-managed, serverless data warehouse. It also explores BigQuery ML, and the processes and key commands that are used to build custom machine learning models. 9 videos1 reading1 assignment1 app item This section explores four different options to build machine learning models on Google Cloud. It also introduces Vertex AI, Google's unified platform for building and managing the lifecycle of ML projects. 8 videos1 reading1 assignment This section focuses on the three key phases--data preparation, model training, and model preparation--of the machine learning workflow in Vertex AI. Learners get the opportunity to practice building a machine learning model with AutoML. 8 videos1 reading1 assignment1 app item This section reviews the topics covered in the course, and provides additional resources for further learning. 1 video

7 modules

Beginner level

https://www.coursera.org/learn/gcp-big-data-ml-fundamentals

95%

Arctic Development

2,314

4.6

Dr. Joshua Evans

University of Alberta

['Urban Planning', 'Northern Geography', 'Arctic', 'environmental science', 'Regional Development']

Welcome to Arctic: Development! In this third in a series of Arctic MOOCs, brought to you by a unique partnership between the University of Alberta and UiT The Arctic University of Norway, we will be exploring regional development in a changing arctic. In this 4-week course, you will investigate the role that natural resources play across the Indigenous, Nordic, Russian and North American Arctics, different strategies for resource management in different regions, and how these affect community planning and development efforts in an increasingly populated part of the world. We'll also see how climate change is dramatically impacting the Arctic, and examine a number of adaptations that different arctic communities are implementing to combat rapid, climate-influenced change. By the end of this course, you will have an idea of the opportunities presented to and difficulties faced by members of northern communities, and gain an understanding of just what regional development looks like in a changing Arctic. Welcome to the first step of your journey in Arctic: Development! In this short, introductory module we'll cover the basics of the Arctic, northern sustainability, geopolitics, resource management and development. To do this, we'll first see how the region is usually viewed through the particular lens of "The Four Arctics". At the end of this module, you'll have the context and vocabulary to tackle some of the issues in resource management, community management, and development, covered in the rest of the course. When it's time to venture north, click on the first video to get started! 5 videos2 readings1 assignment1 discussion prompt Welcome back! Now that you have an understanding of the four Arctics and some of the basic concepts affecting development in these regions, it's time to deep-dive into resource management. In this module we'll first take stock of some of the renewable and non-renewable resources in the Arctic, and explore different resource management strategies employed in each of the four Arctics, encountering a number of "tragedy of the commons" case studies. Finally, you'll reflect upon the formation and function of the Arctic Council, and its role in resource management. 6 videos1 reading4 assignments1 discussion prompt Now that we're aware of some of the resources in the Arctic and how they're managed, it's time to move on to the people that live there. In this module, we'll turn our attention to community planning and development efforts in an increasingly populated Arctic, and how communities in various Arctic regions form resilience to some of the unique problems faced in these regions. 7 videos1 reading5 assignments1 discussion prompt If you're reading this, you've reached the very last module of the course- congratulations! Our previous three modules have given us the background needed to finally tackle the largest question posed in the course: what does development look like in a changing Arctic? In this module, we'll see how climate change is impacting the Arctic, and examine a number of structural and non-structural adaptations that different arctic communities are implementing. Finally, we will look at the strategies and policies directing and maintaining development across the four Arctics in the face of immense environmental change. 4 videos1 reading3 assignments1 discussion prompt

4 modules

Beginner level

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/arctic-development

Project Management Capstone

8,565

4.9

IBM Skills Network Team

IBM

['Project Management', 'Risk Management', 'Agile Management', 'Leadership', 'Scrum (Software Development)']

This capstone project course will give you the chance to practice the work that project managers do in real life when managing projects. You will assume the role of a project manager and gain hands-on experience managing a project from start to finish. You will plan, execute, and close the project. By the end, you will have many artifacts that will showcase both your knowledge of predictive and adaptive methodologies, which can then be added to your portfolio to show employers. As part of this course, you will produce common project deliverables. Artifacts you will create using a predictive methodology include a work breakdown structure, network diagram, budget, quality and communications management plans, and a risk register. Artifacts that showcase your adaptive methodology skills include user stories, examples of product and sprint backlogs, and a burndown chart analysis. You will also produce a project status report, a change form, and a closeout report. This capstone course is a great way to build out your project management portfolio and showcase your skills to prospective employers. In this module, you will review and analyze a comprehensive scenario. You will also review a business case that serves as a key input to develop a project charter. Then, you will go through a Stacey diagramming analysis that supports the project scenario. You will also watch a video that revisits the project charter and stakeholder register templates and development criteria. In this module, you will also participate in a structured lab and create a project charter and stakeholder register, leveraging the given project scenario and business case. Additionally, you will be provided with a potential solution. Lastly, you will take a graded quiz to test your understanding of the key concepts and prepare for the CAPM certification test. 4 videos3 readings2 assignments6 plugins In this module, you will be introduced to some project planning activities, such as a work breakdown structure (WBS), network diagram, high-level budget, quality management plan, communications management plan, and risk register. This module will help you build the predictive project management plan using the project scenario, business case, Stacey diagram analysis and the project charter and stakeholder register developed in the previous module. Lastly, you will take a graded quiz to test your understanding of the key concepts and prepare for the CAPM certification test. 6 videos1 reading4 assignments4 plugins Welcome to module three. Module three introduces the adaptive or Scrum portion of the course. You will develop user stories, a product backlog, and a sprint backlog to support your app development project introduced in module one and the supporting documents developed from module two. Then in the second lesson of the module, you will create a Kanban board using the materials developed in the first lesson of this module. You will also analyze a burndown chart example provided. 3 videos1 reading4 assignments5 plugins Effective status reporting, change management, and closeout are essential to a project’s success. Module four addresses predictive monitoring, controlling, and closeout activities. In this module, you will create a project status report. You will analyze a proposed change to the project and complete a change form to update the status. To close out the module and complete the project, you will complete a closeout report based on a “lessons learned” document. 3 videos1 reading4 assignments6 plugins Welcome to module 5. In this module, you will submit your project, which you have been working on developing in the previous four modules. You will also be required to peer-review another’s project based on the rubric provided. In the bonus content lesson, you will explore the importance of having a personal portfolio and a great resume. A personal portfolio is a great way to share who you are, showcase the work you have accomplished, and demonstrate that you have the skills to excel in a potential new role. Writing a resume can be a challenge. You need your resume to be impactful, share a compelling story, and capture the attention of the reader. In this module, you will learn some helpful tips on how to create an impactful resume and portfolio. 2 videos3 readings1 peer review3 plugins

5 modules

Advanced level

18 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/ibm-project-management-capstone

Azure: Compute, Storage, and Database Security

Enrollment number not found

Rating not found

Whizlabs Instructor

Whizlabs

['Azure Container', 'Azure Disk Encryption (ADE)', 'Azure Kubernetes Service (AKS)', 'Azure SQL Database', 'Access Key']

Azure: Compute, Storage, and Database Security Course is the third course of the Exam Prep AZ-500: Microsoft Azure Security Engineer Associate Specialization. This course is designed to describe the concepts of Azure Compute, Storage, and SQL DB Security related to multiple Azure services. In This course you will learn about planning and implementing advanced security for compute, planning and implementing security for storage, and planning and implementing security for Azure SQL Database and Azure SQL Managed Instance. This course is basically divided into two modules, Lessons and Video Lectures further segment each module. This course facilitates learners with approximately 3:00 - 4:00 Hours of Video lectures that provide both theory and hands-on knowledge. Also, Graded and Ungraded Quizzes are provided with every module in order to test the ability of learners. By the end of this course, you will be able to learn about Advanced Security for Compute Resources, Implement Security for Storage, and Database Services. To be successful in this course, you should have a background in Compute, Storage, and Database related services in Azure. Welcome to Week 1 of the Course. This week, we’ll explore the concepts of Azure Kubernetes and Container services. We will also explore the concepts of Virtual Machine Security, Encryption, and image security. By the end of the course, we'll how to implement Azure Bastion Host and Remote Access Management. 15 videos3 readings3 assignments1 discussion prompt Welcome to Week 2 of the Course. This week, we’ll explore the concepts of Azure Storage Accouts Security Access Conttrol and key Management. By the end of this course, we will be able to learn how to implement SAS, Stored Access Policies, Azure Storage Encryption, Disk Encryptions options and featues. 14 videos1 reading2 assignments Welcome to Week 2 of the Course. This week, we’ll explore the concepts of Azure SQL Database Services Security. We learn about how to working with the SQL DB - Auditing, Data Security, and Data MaskingBy the end of this course, we will be able to learn how to demonstrate and implement the concepts of SQL DB Encryption and Security. 10 videos3 readings2 assignments

3 modules

Intermediate level

8 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/azure-compute-storage-and-database-security

Health Care IT: Challenges and Opportunities

20,770

4.6

Bruce J Darrow, MD, PhD

Icahn School of Medicine at Mount Sinai

[]

A strong argument can be made that the health care field is one of the most information-intensive sectors in the U.S. economy and avoidance of the rapid advances in information technology is no longer an option. Consequently, the study of health care information technology and systems has become central to health care delivery effectiveness. This course covers the modern application of information technology that is critical to supporting the vision and operational knowledge of the health care leaders in managing the health care organization. Heath care decision-makers have to meet head-on the dynamic challenges of health care delivery quality, cost, access, and regulatory control. Additionally, this course integrates the Healthcare Information System as integral to the Quality Assurance Tracking Programs including measurement of systems inputs, processes, and outputs with special emphasis on systems outcomes research and organizational accountability to its various stakeholders, not the least of which are government regulators. 1 video2 readings 1 video 1 video 1 video 1 video1 assignment 2 videos 1 video 1 video1 assignment 3 videos 1 video 1 video 1 video1 assignment 3 videos 1 video 3 videos 1 video 1 video1 assignment 1 video 1 video 1 video 1 video 1 video 1 video1 assignment

23 modules

Intermediate level

https://www.coursera.org/learn/healthcare-it

96%

Reproducible Research

105,323

4.6

Roger D. Peng, PhD

Johns Hopkins University

['Knitr', 'Data Analysis', 'R Programming', 'Markup Language']

This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This course will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results. This week will cover the basic ideas of reproducible research since they may be unfamiliar to some of you. We also cover structuring and organizing a data analysis to help make it more reproducible. I recommend that you watch the videos in the order that they are listed on the web page, but watching the videos out of order isn't going to ruin the story. 9 videos4 readings1 assignment This week we cover some of the core tools for developing reproducible documents. We cover the literate programming tool knitr and show how to integrate it with Markdown to publish reproducible web documents. We also introduce the first peer assessment which will require you to write up a reproducible data analysis using knitr. 9 videos1 assignment1 peer review This week covers what one could call a basic check list for ensuring that a data analysis is reproducible. While it's not absolutely sufficient to follow the check list, it provides a necessary minimum standard that would be applicable to almost any area of analysis. 10 videos This week there are two case studies involving the importance of reproducibility in science for you to watch. 5 videos1 reading1 peer review

4 modules

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/reproducible-research

93%

Cloud Computing Primer for Semi-tech and Business Learners Specialization

1,643

4.7

Anh Le

Codio

['infrastructure as a service', 'Cloud Applications', 'Platform As A Service (PAAS)', 'Software As A Service (SAAS)', 'Cloud Computing', 'infrastructure as a service', 'Cloud Applications', 'Platform As A Service (PAAS)', 'Software As A Service (SAAS)', 'Cloud Computing']

This specialization is intended for semi-technical and business learners who seek to develop a fundamental foundation of cloud computing. In these three courses, you will cover the three main models of cloud computing: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructor as a Service (IaaS) along with public vs. private cloud. The goal of this specialization is to help you determine which models of cloud computing is best for your needs. It will also equip you with the knowledge to tackle more advanced I.T. topics. Applied Learning Project Learners will be exposed to demos of cloud computing models (Software as a Service, Platform as a Service, and Infrastructor as a Service) which mimick some of the most common applications and platforms they may see in the real world. These demos will help learners determine which models are best suited for their needs. Describe at least three advantages and disadvantages of cloud computing Provide a strategy on how an ISV can utilize SaaS to promote their growth Explore the application of a SaaS cloud computing model through a demo engagement Differentiate between platform and platform management Differentiate a public PaaS cloud from a private PaaS cloud Explore a mock environment of a PaaS cloud computing model through a demo engagement Provide three components that are important to consider when selecting a virtual machine Provide at least three different cloud financial model examples and give one benefit of each Engage in a mock experience of an IaaS cloud computing model through a demo

3 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/codio-cloud-computing-primer-semi-technical-business

Business Process Management in Healthcare Organizations

11,351

4.6

Margaret Kilduff, Ph.D.

Rutgers the State University of New Jersey

['Public Health and Wellness Healthcare Organization Operations', 'Pharmacy Healthcare Organization Operations', 'Healthcare Administration', 'Medical Healthcare Organization Operations']

Have you ever needed to resolve a billing or other issue with a healthcare organization and thought that there must be a better, more efficient, and more customer-friendly way to operate such a business process? For example, have you thought that there should be an easier way to read your bill or pay your bill? Or do you work in a healthcare organization and find yourself thinking that there must be better ways for the business processes to function? If you have, this course is for you. Course content includes an overview of healthcare organization business processes including business process management approaches as well as a discussion of healthcare organization entrepreneurship as a business process. The course provides links to external sites to connect you to the larger "real world" of healthcare organization business processes, business process management, and entrepreneurship. The links also serve as resources you can take with you after you complete the course experience. And because everyone loves a road trip/field trip, there are also "virtual field trips" to the often hidden places of interest on the web. The course format is readings, videos, quizzes, and a project. The project requires you to synthesize course material to design patient-centered business processes for a healthcare organization the way you would have things run in the best of all worlds. The design (submitted as an electronic word processing document in memo format) is an artifact of the course which you can circulate to colleagues or use as the basis for a talk or presentation event. This lesson provides an overview of the course as well as an overview of healthcare organization business processes and business process management. 16 readings3 assignments4 discussion prompts7 plugins This lesson provides an overview of healthcare organization business process management improvement and innovation. 10 readings2 assignments2 discussion prompts6 plugins This lesson provides an overview of healthcare organization electronic patient/customer records business processes. 10 readings2 assignments2 discussion prompts6 plugins This lesson is a synthesis of the course material to design patient-centered healthcare organization business processes the way you would have things run in the best of all worlds. 8 readings2 assignments1 peer review4 discussion prompts5 plugins

4 modules

Beginner level

https://www.coursera.org/learn/business-process-management-in-healthcare-organizations

97%

Amazon Redshift Primer

Enrollment number not found

Rating not found

AWS Instructor

Amazon Web Services

[]

This course introduces you to Amazon Redshift, the AWS service that provides cloud-native data warehousing. This course introduces you to the service and its core features and capabilities. You will see how this service integrates with other AWS services and be introduced to important terminology and technology concepts. The course includes a demonstration of Amazon Redshift and provides an assessment to help you gauge how well you understood the concepts covered. 1 reading1 assignment

1 module

1 hour to complete

https://www.coursera.org/learn/aws-amazon-redshift-service-primer

Intermediate Linux Troubleshooting

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['LVM partitions', 'system access troubleshooting', 'disk space management', 'Linux troubleshooting', 'file system troubleshooting']

Take your Linux troubleshooting skills to the next level with this intermediate course designed for experienced IT professionals. The course begins with an in-depth look at system access troubleshooting, addressing common issues such as unreachable servers, problems connecting to websites or applications, and SSH access failures. You'll also learn to resolve firewall issues, troubleshoot terminal client problems, and connect using Putty to a VirtualBox VM. These modules provide practical knowledge and techniques for maintaining robust system access in various scenarios. Next, the course delves into comprehensive file system troubleshooting. You'll tackle challenges like navigating directories, opening files or running scripts, and finding files and directories. Learn how to create links, write to files, and manage file permissions effectively. The course also covers critical topics like handling disk space issues, creating and managing partitions with both standard and LVM methods, and extending disks using LVM. These advanced techniques ensure you can manage file systems efficiently and prevent common issues from escalating into major problems. Finally, you'll explore methods for deleting old files and using scripts for automated file management, addressing file system corruption, and resolving issues with the /etc/fstab file. By the end of this course, you will have mastered intermediate troubleshooting techniques, ready to handle complex Linux issues with confidence and expertise. Whether you're looking to enhance your current skill set or prepare for more advanced roles, this course provides the tools and knowledge necessary for effective Linux troubleshooting. For experienced IT pros and admins to enhance Linux troubleshooting skills. Requires foundational knowledge of Linux commands and operations. In this module, we will focus on troubleshooting system access issues. You'll learn to diagnose and fix problems that prevent server reachability, connect to websites and applications, resolve SSH connection issues, and address firewall problems. Additionally, we will cover terminal client troubleshooting and connectivity issues with VirtualBox VMs using Putty. 7 videos2 readings In this module, we will tackle common filesystem issues in Linux environments. You'll learn to navigate directories, open files, and run scripts. We will cover finding files, creating links, managing file operations, changing permissions, and dealing with disk space issues. Additionally, you will learn to create and manage partitions, extend disk space, delete old files, and handle filesystem corruption. 16 videos1 reading1 assignment

2 modules

Intermediate level

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/packt-intermediate-linux-troubleshooting-mvrrj

IBM Data Topology

3,296

4.8

Mike Hervey

IBM

['Artificial Intelligence (AI)', 'Data Science', 'Digital Strategy', 'Dataflow', 'Strategic Planning']

Every business and organization is facing new challenges with their data. Pressures related to regulation and compliance, leveraging AI, spanning multicloud environments, and increasing volumes of inaccessible data are forcing executives and administrators to either modernize their infrastructures or become obsolete. But moving to the latest technology in a monolithic architecture is a tempting solution that can be expensive and cause more problems than it solves. In this course, you learn how to meet the needs of all your data consumers through the construction of a modern logical topology that helps you optimize data flow. Every business and organization is facing new challenges with their data. Pressures related to regulation and compliance, leveraging AI, spanning multicloud environments, and increasing volumes of inaccessible data are forcing executives and administrators to either modernize their infrastructures or become obsolete. But moving to the latest technology in a monolithic architecture is a tempting solution that can be expensive and cause more problems than it solves. In this course, you learn how to meet the needs of all your data consumers through the construction of a modern logical topology that helps you optimize data flow. 34 videos5 assignments

1 module

Intermediate level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/ibm-data-topology

Introduction to Spreadsheets and Models

119,460

4.2

Don Huesman

University of Pennsylvania

['Monte Carlo Method', 'Microsoft Excel', 'Linear Programming (LP)', 'Solver']

The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have the know-how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future. Through short, easy-to-follow demonstrations, you’ll learn how to use Excel or Sheets so that you can begin to build models and decision trees in future courses in this Specialization. Basic familiarity with, and access to, Excel or Sheets is required. This module was designed to introduce you to the history of spreadsheets, their basic capabilities, and how they can be used to create models. You'll learn the different types of data used in spreadsheets, spreadsheet notations for mathematical operations, common built-in formulas and functions, conditional expressions, relative and absolute references, and how to identify and correct circular references. By the end of this module, you'll understand the context of spreadsheets, be able to navigate a spreadsheet, use built-in formulas and functions in spreadsheets, create your own simple formulas, and identify and correct common errors so you can put spreadsheets to work for you. 6 videos2 readings1 assignment In this module, you'll move from spreadsheet to model, so you can begin to create your own models that reflect real-world events. You'll learn how to organize and lay out model elements, as well as the types of objective functions and their use. You'll also learn what-if analysis and scenarios, sensitivity analysis, and other classic models. By the end of this module, you'll be able to design a spreadsheet reflecting assumptions, decision variables, and outcomes, create a basic cashflow model, evaluate a small business opportunity, conduct what-if analysis, identify key variables using sensitivity analysis, and linear programming models and deterministic models. 6 videos2 readings1 assignment This module was designed to introduce you to how you can use spreadsheets to address uncertainty and probability. You'll learn about random variables, probability distributions, power, exponential, and log functions in model formulas, models for calculating probability trees and decision trees, how to use regression tools to make predictions, as well as multiple regression. By the end of this module, you'll be able to measure correlations between variables using spreadsheet statistical functions, understand the results of functions that calculate correlations, use regression tools to make predictions, and improve forecasts with multiple regression. 6 videos3 readings1 assignment In this module, you'll learn to use spreadsheets to implement Monte Carlo simulations as well as linear programs for optimization. You'll examine the purpose of Monte Carlo simulations, how to implement Monte Carlo simulations in spreadsheets, the types of problems you can address with linear programs and how to implement those linear programs in spreadsheets. By the end of this module, you'll be able to model uncertainty and risk in spreadsheets, and use Excel's solver to optimize resources to reach a desired outcome. You'll also be able to identify the similarities and differences between Excel and Sheets, and be prepared for the next course in the Business and Financial Modeling Specialization. 4 videos3 readings1 assignment

4 modules

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/wharton-introduction-spreadsheets-models

81%

Creative Writing: The Craft of Setting and Description

64,023

4.7

Amity Gaige

Wesleyan University

[]

In this course aspiring writers will be introduced to the techniques that masters of fiction use to ground a story in a concrete world. From the most realist settings to the most fantastical, writers will learn how to describe the physical world in sharp, sensory detail. We will also learn how to build credibility through research, and to use creative meditation exercises to deepen our own understanding of our story worlds, so that our readers can see all that we imagine. Writing a great short story is like conveying a dream. As we will see from studying one famous master, a "persuasive" setting is necessary in order to build mood, character, and even plot. 7 videos4 readings1 peer review Pack your fiction with "vitamin-rich" detail. Looking at the work of both masters and students, we will discuss how funny, meaningful, and powerful details can be. 4 videos3 readings1 peer review Create settings both familiar and unfamiliar to you, while avoiding common missteps. You will be guided through several meditation exercises as you practice "imaginative research". 4 videos1 peer review Setting and description works in realist and non-realist fiction, as well as across literary genres. Consider how to write about your own "primal landscape". 4 videos1 peer review

4 modules

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/craft-of-setting-and-description

95%

Digital Media and Marketing Strategies

135,219

4.6

Mike Yao

University of Illinois Urbana-Champaign

['Brand Communication', 'Social Media', 'Content Marketing', 'Digital Marketing', 'search marketing']

The proliferation of digital technology gives businesses an unprecedented and diverse new set of tools to reach, engage, monitor, and respond to consumers. The aggregated and voluminous digital data can also be leveraged to better target specific consumer segments. Following “Digital Media and Marketing Principles,” this course aims to give you a deeper understanding of core processes of planning a digital marketing campaign and the role of various digital channels in integrated marketing communication. You will be able to: - Adopt a holistic and integrated approach to digital marketing planning - Develop a purposeful content marketing strategy to achieve your business and marketing goals - Effectively mix paid, earned, owned, and shared media channels to discover, reach, and engage your customers - Critically evaluate the role social media platforms play in viral and influencer marketing campaigns - Evaluate and measure the success of digital marketing campaigns - Identify and manage risks in digital marketing This course is part of Gies College of Business’s suite of online programs, including the iMBA and iMSM. Learn more about admission into the program and explore how your Coursera work can be leveraged if accepted into a degree program at https://degrees.giesbusiness.illinois.edu/idegrees/. In this module, you will learn to strategically align business and marketing goals through strategic communication. You will also learn how to evaluate and prepare your digital assets for launching a digital campaign. 9 videos7 readings2 quizzes In this module, you will learn key concepts and tactical considerations in managing online advertising, search optimization, content-based marketing, and CRM to discover and reach prospective consumers. 9 videos3 readings1 quiz1 peer review In this module, you will learn the best ways to engage with audiences on social channels, social media strategy creation and execution, how to plan and execute an email campaign, and effective campaign measurement. 8 videos3 readings1 quiz In this module, you will learn how to strategically select the appropriate KPIs and metrics to evaluate digital campaign success. You will also learn about the challenges and pitfalls in digital marketing. 9 videos4 readings1 quiz1 peer review1 plugin

4 modules

Beginner level

https://www.coursera.org/learn/marketing-plan

95%

Guided Tour of Machine Learning in Finance

35,228

3.8

Igor Halperin

New York University

[]

This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Supervised Machine Learning methods are used in the capstone project to predict bank closures. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance. The goal of Guided Tour of Machine Learning in Finance is to get a sense of what Machine Learning is, what it is for and in how many different financial problems it can be applied to. The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Individuals interested in applications of ML for personal day trading Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course. 11 videos3 readings1 assignment 6 videos3 readings1 assignment1 programming assignment1 ungraded lab 7 videos4 readings1 assignment1 programming assignment1 ungraded lab 9 videos4 readings1 assignment2 programming assignments2 ungraded labs

4 modules

Intermediate level

https://www.coursera.org/learn/guided-tour-machine-learning-finance

83%

Aboriginal Worldviews and Education

29,425

4.7

Jean-Paul Restoule

University of Toronto

[]

Intended for both Aboriginal and non-Aboriginal learners, this course will explore indigenous ways of knowing and how they can benefit all students. Topics include historical, social, and political issues in Aboriginal education; terminology; cultural, spiritual and philosophical themes in Aboriginal worldviews; and how Aboriginal worldviews can inform professional programs and practices, including but not limited to the field of education. Information about the course 2 readings The description goes here 13 videos1 reading1 peer review The description goes here 24 videos1 reading1 assignment The description goes here 11 videos1 reading The description goes here 9 videos1 reading1 assignment This television series aired on Canada's CBC in 2013. Short clips used in the course created a demand from students for more and to see the clips in their original context. We received permission to show the series here. 4 videos These are additional materials that may be of interest. None of this material counts towards your final grade. 7 videos

7 modules

Beginner level

https://www.coursera.org/learn/aboriginal-education

97%

AI Applications in People Management

12,222

4.8

Prasanna Tambe

University of Pennsylvania

[]

In this course, you will learn about Artificial Intelligence and Machine Learning as it applies to HR Management. You will explore concepts related to the role of data in machine learning, AI application, limitations of using data in HR decisions, and how bias can be mitigated using blockchain technology. Machine learning powers are becoming faster and more streamlined, and you will gain firsthand knowledge of how to use current and emerging technology to manage the entire employee lifecycle. Through study and analysis, you will learn how to sift through tremendous volumes of data to identify patterns and make predictions that will be in the best interest of your business. By the end of this course, you'll be able to identify how you can incorporate AI to streamline all HR functions and how to work with data to take advantage of the power of machine learning. In this module, you will learn about the challenges that the HR field has faced prior to the implementation of artificial intelligence as well as the role data and machine learning play in optimizing decision making. You will also learn about the role that training data plays in machine learning, how rule-based systems are used to mimic human intelligence and how they manipulate that data based on those rules. By the end of this module, you will be able to understand the concepts behind artificial intelligence, rule-based systems, and how data science has changed HR Management. 10 videos1 reading1 assignment In this module, you will learn how AI is applied in HR, and how machine learning can change how people are managed within all HR functions. You will learn how artificial intelligence algorithms can be used in various scenarios and how data can be used to make predictions. By the end of this module, you will be able to distinguish how best to use AI algorithms to manage engagement, attrition, and internal career paths. 8 videos1 reading1 assignment In this module, you will examine the challenges that you may face when implementing AI as a tool. You will identify the changing trends in hiring and how that factors into finding the right applicants and how to best apply AI in hiring decisions. By the end of this module, you will be able to determine how to balance machine-driven decisions and input from supervisors to select the best candidates. 6 videos1 reading1 assignment1 peer review In this module, you will learn about biases that exist within algorithms and how to manage and avoid data adequacy bias. You will also learn how to understand and interpret results, use blockchain to keep data private and secure and understand the transformative nature of blockchain technology. By the end of this module, you will be able to explain how data science and AI have markedly changed the way we approach HR and incorporate emerging technological solutions to structure people management. 14 videos1 reading1 assignment

4 modules

9 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/wharton-ai-applications-people-management

Hadoop Platform and Application Framework

149,689

4.0

Natasha Balac, Ph.D.

University of California San Diego

['Python Programming', 'Apache Hadoop', 'Mapreduce', 'Apache Spark']

This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process. Welcome to the first module of the Big Data Platform course. This first module will provide insight into Big Data Hype, its technologies opportunities and challenges. We will take a deeper look into the Hadoop stack and tool and technologies associated with Big Data solutions. 7 videos4 readings1 assignment In this module we will take a detailed look at the Hadoop stack ranging from the basic HDFS components, to application execution frameworks, and languages, services. 10 videos6 readings3 assignments In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance and robustness, and get an overview of the different ways you can access data on HDFS. 9 videos5 readings3 assignments This module will introduce Map/Reduce concepts and practice. You will learn about the big idea of Map/Reduce and you will learn how to design, implement, and execute tasks in the map/reduce framework. You will also learn the trade-offs in map/reduce and how that motivates other tools. 9 videos3 readings1 assignment2 programming assignments Welcome to module 5, Introduction to Spark, this week we will focus on the Apache Spark cluster computing framework, an important contender of Hadoop MapReduce in the Big Data Arena. Spark provides great performance advantages over Hadoop MapReduce,especially for iterative algorithms, thanks to in-memory caching. Also, gives Data Scientists an easier way to write their analysis pipeline in Python and Scala,even providing interactive shells to play live with data. 10 videos4 readings3 assignments2 programming assignments

5 modules

25 hours to complete (3 weeks at 8 hours a week)

https://www.coursera.org/learn/hadoop

83%

Intro to Analytic Thinking, Data Science, and Data Mining

9,525

4.2

Julie Pai

University of California, Irvine

['Environmental Data Analysis', 'Data Documentation', 'Geophysical Data', 'Data Mining']

Welcome to Introduction to Analytic Thinking, Data Science, and Data Mining. In this course, we will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. We will review the types of business problems data science can solve and discuss the application of the CRISP-DM process to data mining efforts. A brief overview of Descriptive, Predictive, and Prescriptive Analytics will be provided, and we will conclude the course with an exploratory activity to learn more about the tools and resources you might find in a data science toolkit. Welcome to Module 1, Data Science: The Field and Profession. In this module, we will review data science as a field and explore the concepts of small and big data. We will also survey the skills of successful data scientists and discuss the types of business problems data scientists might be asked to solve in the near future. 2 readings1 discussion prompt Welcome to Module 2, Data Science in Business. In this module, we will take a closer look at the applications of data science in a business environment and discuss ethical considerations to keep in mind when working with data. 1 video2 readings1 assignment Welcome to Module 3, Data Mining and an Overview of Data Analytics. In this module we will begin with an explanation of CRISP-DM, a cross-industry standard process for data mining. We will also provide an introduction to descriptive, predictive and prescriptive analytics. 2 readings1 discussion prompt Welcome to Module 4, Solving Problems with Data Science. In this last module of the course we will explore some real-world applications of data science solutions and take a closer look at the types of tools and programs you might expect to see in a data science toolkit. 1 video2 readings1 assignment1 discussion prompt

4 modules

Intermediate level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/intro-analyticthinking-datascience-datamining

The Nurse's Toolkit

2,117

Rating not found

Dr. Deborah Lee

University of Michigan

['healthcare', 'Nursing', 'Nursing Skills', 'Patient care treatment', 'Emergency care']

The Nurse’s Toolkit will introduce learners to various life-saving nursing skills and interventions. Learn critical life-saving concepts and skills related to airway management, trauma, immobilization and splinting, sepsis management, wound care, and obstetrical emergencies. This course also integrates augmented reality into two modules: airways and immobilization, and splinting. The augmented reality will be powered through the learner’s mobile device via a web-based tool that will provide simulations and test learners’ knowledge of the material. In the first module of the Nurse's Toolkit, you will be introduced to your course instructors, review course objectives in the syllabus, introduce yourself to your fellow learners, and take the course pre-survey. You will then dive into your first lesson on airway management with your instructor, Deb Lee. Specifically, you will learn about airway anatomy, airway assessment, common airway complications, and recommended treatment options. 10 videos9 readings1 assignment2 app items1 discussion prompt1 plugin In the second module, you will hear from Ray Blush on how traumatic injuries can be assessed and treated. Specifically, you will hear about the ABCDEF model of trauma: airway, breathing, circulation, disability, exposure, and full set of vitals. 9 videos3 readings1 assignment1 app item1 plugin In the third module, you will hear again from Ray Blush on the topic of immobilization and splinting. You will learn about key concepts like bone anatomy and formation, fractures, and key considerations during the immobilization and splinting process. 6 videos5 readings1 assignment2 app items1 plugin In the fourth module, Melissa Bathish will give you an overview of sepsis including: risk factors, signs and symptoms, assessment, interventions, and re-assessment. 8 videos3 readings1 assignment1 app item1 plugin In the fifth module, Deb Lee returns to give you a deep dive into wounds and burns. This includes characterizing, assessing, and treating wounds. 6 videos3 readings1 assignment1 app item1 plugin In the final module of the Nurse's Toolkit, you will hear from Jeri Antilla on the topic of obstetrical emergencies. You will learn about a variety of topics in this section: post partum hemorrhaging (PPH), hypertensive disorders, and important mental health considerations. 6 videos3 readings1 assignment1 app item

6 modules

16 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/the-nurses-toolkit

Measurement and Analysis

2,868

4.6

Unilever Team

Unilever

['Web Analytics', 'SEO optimization', 'Google Analytics 4', 'RACE Planning Framework', 'Value Propositions']

The Measurement and Analysis course delves into the essential aspects of tracking, analyzing, and optimizing marketing efforts to drive success. Throughout the course, you will gain a solid understanding of search engine marketing (SEM) and search engine optimization (SEO), web analytics and tools, social media platforms and analytics, as well as A/B testing and campaign performance reporting. After completing this course, you will be able to: - Set up an SEO objective and perform keyword research. - Construct and apply a value proposition and identify how to analyze performance of SEO strategy. - Define web analytics and associated KPIs. - Identify key features of the Google Analytics Platform, set up a Google Analytics Dashboard and describe other popular platforms and their key features. - Define the 4Cs of social media marketing and recognize SMART objectives. - Describe the RACE Planning Framework. - Identify top social media platforms and assess the best platform to use for a given strategy and objective. - Design a campaign strategy end-to-end and identify where to automate monitoring and adjusting. - Identify the steps to implement testing for a campaign strategy and plan for performance testing. In this module, you will explore how to differentiate between SEM and SEO, set up SEO objectives, perform keyword research, and analyze the performance of your SEO strategy. 11 videos6 readings6 assignments In this module, you will explore web analytics tools, including the popular Google Analytics platform, and how to set up a comprehensive dashboard for monitoring website performance. 11 videos17 readings5 assignments In this module, you will explore social media marketing, SMART objectives, and the RACE planning framework to help you develop effective social media campaigns and assess platform suitability. 7 videos4 readings5 assignments1 discussion prompt In this module, you will you will gain insights into designing end-to-end campaign strategies, leveraging AI for monitoring and adjustment, implementing A/B testing, and conducting in-depth performance analysis. 10 videos6 readings7 assignments

4 modules

Beginner level

27 hours to complete (3 weeks at 9 hours a week)

https://www.coursera.org/learn/measurement-and-analysis

Using Databases with Python

503,187

4.8

Charles Russell Severance

University of Michigan

['Python Programming', 'Database (DBMS)', 'Sqlite', 'SQL']

This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization. This course will cover Chapters 14-15 of the book “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-13 of the textbook and the first three courses in this specialization. This course covers Python 3. To start this class out we cover the basics of Object Oriented Python. We won't be writing our own objects, but since many of the things we use like BeautifulSoup, strings, dictionaries, database connections all use Object Oriented (OO) patterns we should at least understand some of its patterns and terminology. 12 videos4 readings2 assignments We learn the four core CRUD operations (Create, Read, Update, and Delete) to manage data stored in a database. 6 videos1 assignment2 app items In this section we learn about how data is stored across multiple tables in a database and how rows are linked (i.e., we establish relationships) in the database. 8 videos1 assignment1 app item In this section we explore how to model situations like students enrolling in courses where each course has many students and each student is enrolled in many courses. 4 videos1 assignment1 app item In this section, we put it all together, retrieve and process some data and then use the OpenStreetMaps API to visualize our data. 5 videos3 readings1 app item

5 modules

Beginner level

https://www.coursera.org/learn/python-databases

96%