Foundations of Machine Learning

Foundations of Machine Learning

MET CS 555 (4 credits)

Prerequisites: MET CS 544 or MET CS 550 or consent of instructor. Learn the foundations of machine learning, regression, and classification. Topics include how to describe data, statistical inference, 1 and 2 sample tests of means and proportions, simple linear regression, multiple linear regression, multinomial regression, logistic regression, analysis of variance, and regression diagnostics. These topics are explored using the statistical package R, with a focus on understanding how to use these methods and interpret their outputs and how to visualize the results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results are discussed. Concepts are presented in context of real-world examples in order to help you learn when and how to deploy different methods.

2026SPRGMETCS555A1, Jan 20th to Apr 30th 2026

2026SPRGMETCS555A2, Jan 20th to Apr 30th 2026

2026SPRGMETCS555O2, Mar 10th to Apr 27th 2026