Introduction to Artificial Intelligence CMPT 310 (3)

Artificial intelligence is an area with vast application scenarios. This course is intended as a prerequisite for advanced-level AI courses and covers the fundamental concepts and foundational mathematical formulations in machine learning and AI. Topics include supervised learning, linear regression, gradient descent, search algorithms, Markov decision processes, and Bayes nets. Prerequisite: CMPT 225 and (STAT 271 or ENSC 280), all with a minimum grade of C-. Recommended: MATH 251. Students with credit for CMPT 311 may not take this course for further credit.