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DATS344 - Probabilistic Graphical Models

Course Details

Course Code: DATS344 Course ID: 5143 Credit Hours: 3 Level: Undergraduate

This course focuses on the use of probabilistic graphical models to represent complex domains using probability distributions. Using probabilistic graphical models to model large collections of random variables with complex interactions. Students will learn the key formalisms and main techniques in building probabilistic graphical models. And, how to use them to make predictions and support decision-making under uncertainty. Bayesian networks, directed and undirected graphical models, as well as their temporal extensions will be covered. Students will be introduced to causation and how it can be modeled. (Prerequisites: MATH302, MATH328, DATS301)

Course Schedule

Registration Dates Course Dates Start Month Session Weeks
Registration06/29/2026 - 12/04/2026 Course Dates12/07/2026 - 01/31/2027 Start Month December SessionFall 2026 Session D Weeks8 Week session

Previous Syllabi

Not current for future courses.