Foundations of Machine Learning

MET CS 555

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.

FALL 2023 Schedule

Section Instructor Location Schedule Notes
A1 Wu CAS 233 M 6:00 pm-8:45 pm

FALL 2023 Schedule

Section Instructor Location Schedule Notes
A2 Alizadeh-Sha CAS 213 R 6:00 pm-8:45 pm

FALL 2023 Schedule

Section Instructor Location Schedule Notes
A3 Alizadeh-Sha MET 101 R 9:00 am-11:45 am

FALL 2023 Schedule

Section Instructor Location Schedule Notes
O2 Alizadeh-Sha ROOM ARR TBD-TBD On-line course

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
A1 Zhang CAS 315 T 12:30 pm-3:15 pm Class Full

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
A2 Alizadeh-Sha CAS 315 R 12:30 pm-3:15 pm

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
A3 Alizadeh-Sha FLR 152 R 6:00 pm-8:45 pm

SPRG 2024 Schedule

Section Instructor Location Schedule Notes
O1 Alizadeh-Sha ROOM ARR TBD-TBD On-line course

Note: this course was also offered during Summer Term

Note that this information may change at any time. Please visit the Student Link for the most up-to-date course information.