MATH 475 Models and Simulation for Data Science
This course develops advanced statistical topicsrelevant to data science. Topics include multiplelinear, general linear, and logistic regression;transforming data; Monte Carlo simulation ofstochastic systems; re-sampling based inference(bootstrap, etc.); likelihood theory and Bayesianmethods; model selection and performance.
Prerequisite
A “C” or better in MATH 316 and in CS 160 or CS 170