Practices Week 1 - February 13 - No lecture Week 2 - February 20 - MLOps pipeline Week 3 - February 27 - MLOps pipeline Week 4 - March 6 - Dataset Versioning Week 5 - March 13 - Track and Compare Model Experiments Week 6 - March 20 - Containerize an ML Model Week 7 - March 27 - Deploy a Machine Learning Model Week 8 - April 3 - Monitor Data Drift Week 9 - April 10 - Automate ML Workflow Week 10 - April 17 - Deploy a Model Week 11 - April 24 - Reading assignment/guest lecture Week 12 - May 1 - Reading assignment/guest lecture Week 13 - May 8 - Time for projects Week 14 - May 15 - Time for projects Week 15 - May 22 - Oral Exam/ Presentation
