Data Science
Advanced Machine Learning
1 credits
Neural networks trained with backpropagation. Deep learning. Overfitting and underfitting. Active data acquisition. Hyperparameter optimization.
Average
90.2%
Students
717
Sections
10
Grade distribution. <50: 0, 50-54: 0, 55-59: 0, 60-63: 2, 64-67: 4, 68-71: 2, 72-75: 22, 76-79: 21, 80-84: 70, 85-89: 133, 90-100: 458.
Historical Averages
2016–2024
Lowest section avg
82.0%
Highest section avg
94.2%
Terms offered
9
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 |
|---|---|---|---|---|
| 001 | Lecture | Open | Tue 09:30-11:00, Thu 09:30-11:00 | Elham E Khoda |
| 002 | Lecture | Open | Mon 11:00-12:30, Wed 11:00-12:30 | Varada Kolhatkar |
| L01 | Laboratory | Open | Tue 14:00-16:00 | Elham E Khoda |
| L02 | Laboratory | Open | Thu 14:00-16:00 | Elham E Khoda |
| L03 | Laboratory | Open | Mon 14:00-16:00 | Varada Kolhatkar |
| L04 | Laboratory | Open | Wed 14:00-16:00 | Varada Kolhatkar |
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