In this paper, we present the methodology for the introduction to scientific computing based on model-centered learning. We propose multiphase queueing systems as a basis for learning objects. We use Python and parallel programming for implementing the models and present the computer code and results of stochastic simulations.
['Vladimiras Dolgopolovas', 'Valentina Dagienė', 'Saulius Minkevičius', 'Leonidas Sakalauskas']
Python for scientific computing education: Modeling of queueing systems