This course is aimed at students with some prior programming experience in Python and a rudimentary knowledge of computational complexity. The goal is to provide students with a brief introduction to many topics, so that they will have an idea of what’s possible when the time comes later in their career to think about how to use computation to accomplish some goal.
Students will spend a considerable amount of time writing programs to implement the concepts covered in the course. Topics covered include plotting, stochastic programs, probability and statistics, random walks, Monte Carlo simulations, modeling data, optimization problems, and clustering.
What will you learn?
If you successfully complete this course, you will have:
Full time/Part time