DSC 521 - Machine Learning I

Course Description: Introduction to machine learning and applications with implementation in computer languages such as Python, R, SAS, and Matlab. Topics include review of linear algebra, basic optimization techniques, and classification and clustering algorithms such as principal component analysis, singular value decomposition, decision trees, and neural networks. Six lecture hours and two laboratory hours per week for each week of the half-semester session.

Credit Hours: 3

Corequisite Courses: None
Prerequisite Courses: None
Additional Restrictions/ Requirements: None
Course Repeatability: Course may not be repeated

ADDITIONAL COURSE INFORMATION

Equivalent Courses: None
Undergraduate Crosslisting: None
Additional Course Fees: MS Data Science Program Fee Additional Fee Amounts
Course Attribute: None

Click here for the Spring 2025 Class Schedule.