Module 1 · Building ML Systems

Weeks 1–6. Building end-to-end ML systems for real problems — scoping, formulation, validation, metrics, features, and pipelines.

Session descriptions, readings, and slides live on the schedule so there’s a single place to keep them up to date. Links below go straight to each session.

Sessions

Session	Date
Class overview	Tue Aug 25
Why ML systems can fail in practice	Thu Aug 27
Scoping ML systems	Tue Sep 1
ML systems in practice — student presentations	Thu Sep 3
Analytical formulation and baselines	Tue Sep 8
Data exploration	Thu Sep 10
Model selection (evaluation)	Thu Sep 17
Model performance metrics	Tue Sep 22
Feature engineering	Thu Sep 24
ML modeling in practice & hyperparameter tuning	Tue Sep 29
ML pipelines	Thu Oct 1

Project sessions in this stretch: project pitches (Sep 15) and update presentations (Oct 6 & 8).