We describe a novel, interdisciplinary, computational methods course that uses Python and associated numerical and visualization libraries to enable students to implement simulations for a number of different course modules. Problems in complex networks, biomechanics, pattern formation, and gene regulation are highlighted to illustrate the breadth and flexibility of Python-powered computational environments.
@article{arxiv.0704.3182,
title = {Python for Education: Computational Methods for Nonlinear Systems},
author = {Christopher R. Myers and James. P. Sethna},
journal= {arXiv preprint arXiv:0704.3182},
year = {2007}
}