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.

2023FALLMETCS555 A1, Sep 11th to Dec 11th 2023

Days Start End Type Bldg Room
M 06:00 PM 08:45 PM CAS 233

2023FALLMETCS555 A2, Sep 7th to Dec 7th 2023

Days Start End Type Bldg Room
R 06:00 PM 08:45 PM EPC 204

2023FALLMETCS555 A3, Sep 7th to Dec 7th 2023

Days Start End Type Bldg Room
R 09:00 AM 11:45 AM MET 101

2023FALLMETCS555 O2, Oct 31st to Dec 18th 2023

Days Start End Type Bldg Room
ARR TBD TBD ROOM

2023SUM2METCS555SB1, Jul 5th to Aug 14th 2023

Days Start End Type Bldg Room
MW 06:00 PM 09:30 PM MCS B37

2023SUM2METCS555SO2, Jul 5th to Aug 22nd 2023

Days Start End Type Bldg Room
ARR TBD TBD ROOM

Format & Syllabus: