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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)





Prerequisites

Course Schedule

No Course Offerings.

Current Syllabi

Information is provided in the syllabus when the course begins.
Information is provided in the syllabus when the course begins.
Information is provided in the syllabus when the course begins.

No Syllabi Found

Previous Syllabi

Not current for future courses.