Linear Models and Predictive Analytics

Catalog description

This course is designed to provide students with a solid statistical foundation. It covers the core theory and practical applications of linear models and fundamental predictive analytics techniques. Topics covered include generalized linear models (GLMs), data visualization, principal component analysis (PCA) for reducing dimensions, penalized regression, and nonlinear regression.