Data Science
Supervised Learning I
1 credits
Decision trees. k-th nearest neighbour classifiers. Naive Bayes classifiers. Logistic regression.
Average
88.4%
Students
920
Sections
10
Grade distribution. <50: 1, 50-54: 0, 55-59: 1, 60-63: 3, 64-67: 9, 68-71: 8, 72-75: 19, 76-79: 38, 80-84: 113, 85-89: 236, 90-100: 482.
Historical Averages
2016–2024
Lowest section avg
84.0%
Highest section avg
91.8%
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 08:00-09:30, Thu 08:00-09:30 | Varada Kolhatkar |
| 002 | Lecture | Open | Mon 09:30-11:00, Wed 09:30-11:00 | Varada Kolhatkar |
| L01 | Laboratory | Open | Tue 14:00-16:00 | Varada Kolhatkar |
| L02 | Laboratory | Open | Thu 14:00-16:00 | Varada Kolhatkar |
| L03 | Laboratory | Open | Mon 14:00-16:00 | Varada Kolhatkar |
| L04 | Laboratory | Open | Wed 14:00-16:00 | Varada Kolhatkar |
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