Computer Science · Fall 2026
SDSU CS 549 — Machine Learning
Algorithms and computer methods for machine learning. Supervised methods: convolutional neural networks, feedforward neural networks, linear regression, logistic regression, support vector machine; unsupervised methods: dimensionality reduction, k-means clustering, subspace learning. Applications in classification, regression and visualization.
Course requirements
Prerequisites: CS 210 and MATH 254.
- CS 210 and MATH 254.
Fall 2026 enrollment options
Seat status can change| Class # | Format | Status | Seats | Time | Location | Professor | RateMyProfessors |
|---|---|---|---|---|---|---|---|
| 4113 Lrg Lect | In person | Open | 41 / 60 | Tue/Thu 5:30 PM–6:45 PM | OP 201 | Irfan Khan | 3.2/5 · 9 reviews Difficulty 3.6 · 60% take again |
| 8673 Lrg Lect | In person | Open | 65 / 68 | Mon/Wed 2:00 PM–3:15 PM | PSFA 350 | Joann Chen | 4.0/5 · 4 reviews Difficulty 3.8 · 100% take again |
| 9873 Lrg Lect | In person | Open | 67 / 70 | Tue/Thu 5:00 PM–6:15 PM | GMCS 301 | Xin Zhang | No RateMyProfessor match available |