MATH-427 Scientific Programming with Python (3)

Sound quantitative approaches to scientific problems tend to require both programming skills and mathematical knowledge. This course examines the entire process of problem solving from analyzing a practical problem to producing well-structured and well-commented code. It emphasizes development of programming skills for mathematical and statistical problems using Python with NumPy, rSciPy, and R. Includes multiarrays, matrices (not assuming knowledge of linear algebra), numerical methods, maximum likelihood, Bayesian methods, Bootstrap methods, and plotting. Prerequisite: CSC-148 and MATH-221.