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Level 1 · Enrolled

ML Pipelines & Feature Stores

Syllabus · 12 units · ~1 month

Every unit this programme teaches, in the order it is taught. Headlines only — the material itself opens once you are enrolled.

1. Unit 1 Why a Pipeline at All
2. Unit 2 Reproducible Training, From First Principles
3. Unit 3 Data & Model Versioning
4. Unit 4 Orchestration & DAGs: Airflow
5. Unit 5 Scheduling, Backfill & Idempotency
6. Unit 6 Feature Engineering as a Pipeline Stage
7. Unit 7 Feature Stores
8. Unit 8 Experiment Tracking with MLflow
9. Unit 9 The Model Registry & Promotion
10. Unit 10 CI/CD for Models
11. Unit 11 Kubeflow & the Cluster-Native Model
12. Unit 12 Capstone: One Reproducible Pipeline, End to End