AI-Related Courses at UBC

Updated August 2023.  We do not guarantee that every AI-related course at UBC has been listed.


Course Instructor
Business Applications of Machine Learning (BAIT 509) Quan Nguyen
Trends in Computational Linguistics (COLX 585) Muhammad Abdul-Mageed
Machine Learning with Engineering Applications (CPEN 355) Xiaoxiao Li
Deep Learning (CPEN 455) Renjie Liao
Introduction to Artificial Intelligence (CPSC 322) Jordon Johnson
Applied Machine Learning (CPSC 330 ) Andrew Roth
Machine Learning and Data Mining (CPSC 340) Jeff Clune
Machine Learning and Data Mining (CPSC 340) Mark Schmidt
Computational Optimization (CPSC 406) Michael Friedlander
Advanced Machine Learning (CPSC 440) Danica Sutherland
Artificial Intelligence II (CPSC 522) David Poole
Computer Graphics: Modelling (CPSC 524) Alla Sheffer
Topics in Artificial Intelligence - HUMAN-CENTRED AI (CPSC 532C) Cristina Conati
Topics in AI: STAT LEARN THRY (CPSC 532D) Danica Sutherland
Topics in Artificial Intelligence - NLP COMMONSENSE (CPSC 532V) Vered Shwartz
Topics in AI: Causal Inference in Machine Learning (CAUSAL ML) (CPSC 532Y) Mathias Lecuyer
Topics in Computer Graphics - VISUAL AI (CPSC 533R) Helge Rhodin
Topics in Computer Graphics - LEARNING TO MOVE (CPSC 533V) Michiel van de Panne
Topics in Computer Graphics: Visual Geometry with Deep Learning (Deep Vis. Geom.) (CPSC 533Y) Kwang Moo Yi
Topics in Algorithms and Complexity: Optimization Theory (OPTIM THEORY) (CPSC 536M) Michael Friedlander
Topics in Algorithms and Complexity: Submodular Optimization (SUBMODULAR OPT) (CPSC 536S) Bruce Shepherd
Topics in Computer Systems - CAUSAL ML (CPSC 538L) Mathias Lecuyer
Machine Learning (cross-listed with CPSC 340) (CPSC 540) Mark Schmidt
Algorithms for Bioinformatics (CPSC 545) Jiarui Ding
Topics in Human-Computer Interaction - HUMAN-CENTRED AI (CPSC 554C) Cristina Conati
Topics in Human-Computer Interaction - ML & SIGNALS (CPSC 554X) Robert Xiao
Privacy, Ethics, and Security (DSCI 541) Joel Ostblom
Unsupervised Learning (DSCI 563) Varada Kolhatkar
Supervised Learning I (DSCI 571) Varada Kolhatkar
Supervised Learning II (DSCI 572) Varada Kolhatkar
Advanced Machine Learning (DSCI 575) Varada Kolhatkar
Computational Methods in Macroeconomics (ECON 408) Jesse Perla
Advanced Econometrics (ECON 425) Hiroyuki Kasahara
Quantitative Economics with Data Science Applications (ECON 526) Jesse Perla
Computational Economics with Data Science Applications (ECON 622) Jesse Perla
From Exploring to Building Machine Learning Models (EECE 568) Matthew Yedlin
Fundamentals of Visual Computing (EECE 570) Xiaoxiao Li
Electrical Engineering Seminar and Special Problems - CONVEX OPTMIZATN (EECE 571Z ) Christos Thrampoulidis
Computational Methods in Geological Engineering (EOSC 213) Eldad Haber
Nonlinear Inverse Theory (EOSC 555B) Eldad Haber
AI and Machine Learning Applications in Manufacturing (MANU 465) Ahmad Mohammadpanah
Introduction to Mathematical Modelling (MATH 360) Lindsey Daniels
Applied Geostatistics (MINE 420) Ilija Miskovic
Industrial Expert Systems (MINE 547) Ilija Miskovic
Mining Geostatistics (MINE 552) Ilija Miskovic
Machine Learning for Physics and Astronomy Data Analysis (PHYS 310) Joerg Rottler
Data and Society (SOCI 280) Laura Nelson
Special Topics in Statistics - BAYESIAN STATS (STAT 447C) Alexandre Bouchard-Cote
Statistical Inference I (STAT 460) Benjamin Bloem-Reddy
Topics in Bayesian Analysis and Decision Theory (STAT 520P) Geoff Pleiss
Topics in Statistics - PROB OF STATS (STAT 547C) Alexandre Bouchard-Cote
Statistical Theory I (STAT 560) Benjamin Bloem-Reddy