Module 13
Capstones, Portfolio & Interviews
Nothing here is optional. Four finished projects beat twelve finished courses in every hiring conversation.
8 topics ~120 h estimated learning time
Comes after05. Classical Machine Learning
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- 13.1 Capstone 1 — tabular ML, deployed
Core · 20 h
- 13.2 Capstone 2 — vision or audio system
Core · 20 h
- 13.3 Capstone 3 — RAG over a real corpus
Core · 20 h
- 13.4 Capstone 4 — an agent with tools and evals
Advanced · 20 h
- 13.5 Portfolio and writing
Core · 8 h
- 13.6 ML system design interviews
Advanced · 10 h
- 13.7 Coding and ML theory interviews
Core · 12 h
- 13.8 Kaggle and open source
Core · 10 h