DATA 4465 - Machine Learning

Credit(s): 3
Lecture Hour(s): 3
Lecture Hours Schedule Type: Lecture
Tutorial Hour(s): 1

This course will teach how to implement and apply machine learning algorithms. The emphasis will be on practical skills, and the course will focus on giving students skills to make these algorithms work. Students will learn about commonly used learning techniques including supervised and unsupervised learning techniques. Performance evaluation and model selection techniques will be discussed in this course. Students will gain hands-on experience through course assignments and projects.

Prerequisite(s): MATH 2303, MATH 3552, DATA 3453 and DATA 3463, each with a minimum grade of C-.