Foundations of Machine Learning


Foundations of Machine Learning

MET CS 555 (4 credits)

Formerly titled CS 555 Data Analysis and Visualization with R.
This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis. These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize 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. Recommended Prerequisite: MET CS 544 or equivalent knowledge, or instructor's consent.

2025FALLMETCS555A1, Sep 2nd to Dec 10th 2025

Days Start End Type Bldg Room
T 06:00 PM 08:45 PM CGS 515

2025FALLMETCS555A3, Sep 2nd to Dec 10th 2025

Days Start End Type Bldg Room
M 02:30 PM 05:15 PM SOC B63

2025FALLMETCS555A4, Sep 2nd to Dec 10th 2025

Days Start End Type Bldg Room
W 06:00 PM 08:45 PM KCB 104

2025FALLMETCS555O2, Oct 28th to Dec 15th 2025

Days Start End Type Bldg Room
ARR 12:00 AM 12:00 AM

Format & Syllabus: