Computer Science
Advanced Machine Learning
3 credits
Advanced machine learning techniques focusing on probabilistic models. Deep learning and differentiable programming, exponential families and Bayesian inference, probabilistic graphical models and other generative models, Monte Carlo and variational inference methods.
Average
88.7%
Students
501
Sections
6
Grade distribution. <50: 2, 50-54: 0, 55-59: 3, 60-63: 5, 64-67: 4, 68-71: 3, 72-75: 14, 76-79: 19, 80-84: 43, 85-89: 109, 90-100: 290.
Historical Averages
2020–2025
Lowest section avg
84.1%
Highest section avg
91.9%
Terms offered
6
Some grade ranges were withheld by UBC to protect student privacy and are not shown above.
Grade data from ubc-pair-grade-data.
| Section | Activity | Status | Time | Instructor |
|---|---|---|---|---|
| 201 | Lecture | Open | Mon 13:30-15:00, Wed 13:30-15:00 | Mi Jung Park |
| T2A | Discussion | Full | Wed 17:00-18:00 | — |
| T2B | Discussion | Open | Tue 15:30-16:30 | — |
| T2Z | Discussion | Open | — | — |
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