Mathematics - Computational Data Science

Catalog description

This course provides an introduction to topics in data science and machine learning with an emphasis on computation and applications. Programming for the course uses the student's choice of Matlab, Python, or R. Topics covered include dimension reduction, regression techniques, density estimation, machine learning, data assimilation, and clustering and classification techniques. Prerequisite: MATH 290 or equivalent.