Description

A broad introduction into the theoretical foundations and essential algorithms for supervised and unsupervised learning with a focus on best practices and real-world problems.

Requisites

Prerequisites: CS 3270 Minimum Grade: C and MATH 3203

Course Hours

Lecture Hours: 2.00 Lab Hours: 2.00Total Hours: 3.00

Semesters

Fall 2026 Semester
Course Title Instructor Campus Section Syllabus Learning Management System
Machine Learning Foundations Ana Stanescu, Ph.D. Carrollton 01 external Syllabus via Concourse External Resource Course Section External Resource