Overview
This table will be updated weekly with links to course materials (lecture handouts, lab manuals) and due dates as we progress through the course.
| Week | Lecture slides | Lab | Deadlines |
|---|---|---|---|
| 1 (1/26) | Hello, Chameleon Hello, Linux | ||
| 2 (2/2) | Cloud computing on Chameleon | ||
| 3 (2/9) | Build an MLOps pipeline on Chameleon | ||
| 4 (2/17) | Persistent storage on Chameleon | ||
| 5 (2/23) | Large-scale model training on Chameleon | ||
| 6 (3/2) | Train ML models with MLFlow and Ray | ||
| 7 (3/9) | Model optimizations for serving Serving on edge devices System optimizations for model serving | ||
| 8 (3/30) | Offline evaluation of ML systems Online evaluation of ML systems Closing the feedback loop | ||
| 9 (4/6) | |||
| 10 (4/13) |