CSE 250A. Principles of Artificial Intelligence: Probabilistic Reasoning and Learning (4 units)
Link to catalog page: https://catalog.ucsd.edu/courses/CSE.html#cse250a
Description
Methods based on probability theory for reasoning and learning under uncertainty. Content may include directed and undirected probabilistic graphical models, exact and approximate inference, latent variables, expectation-maximization, hidden Markov models, Markov decision processes, applications to vision, robotics, speech, and/or text. Recommended preparation: CSE 103 or similar course. Prerequisites: graduate standing in CSE or consent of instructor.
Prerequisite courses
CSE 250A has no prerequisite courses.
Successor courses
No courses have CSE 250A as a prerequisite.