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.
CITATION STYLE
Dolgopolovas, V., Dagiene, V., Minkevičius, S., & Sakalauskas, L. (2014). Python for scientific computing education: Modeling of queueing systems. Scientific Programming, 22(1), 37–51. https://doi.org/10.1155/2014/164306
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