CS638: Applied Machine Learning

Credits: 3

Catalog Description

This course presents the practical side of machine learning for applications, such as pattern recognition from images or building predictive classifiers. Topics will include linear models for regression, decision trees, rule based classification, support vector machines, Bayesian networks, and clustering. The emphasis of the course will be on the hands-on application of machine learning to a variety of problems. This course does not assume any prior exposure to machine learning theory or practice.

Current & Upcoming Offerings

2025-2026

Fall 2025 1 section
Section Schedule / Time Instructor Location
01
MW 04:00PM - 05:15PM
Babur, Ozgun
M01-0207
Spring 2026 1 section
Section Schedule / Time Instructor Location
01
MW 02:30PM - 03:45PM
TBA
M02-0404

Prerequisites

Notes

This course is co-taught with CS438.

Graduate course in applied machine learning for graduate students covering practical machine learning methods and applications.