Schedule & syllabus

The lecture slides, notes, tutorials, and assignments will be posted online here as the course progresses.
Lecture times are 3:15 - 4:45pm PST. All deadlines are at 11:59pm PST.

This schedule is subject to change according to the pace of the class.

See Past course for the last year's lectures.


Date Description Materials Events
Mon Jan 3 Understanding machine learning production Lecture note
Lecture slides
Lessons learned from 150 ML models at Booking.com
Lecture
Wed Jan 5 ML and Data Systems Fundamentals Lecture note
Lecture slides
Case study: Predict Value of Homes On Airbnb
Breakout exercise: Designing Twitter's Trending Hashtags
Lecture
Mon Jan 10 Training Data Lecture note
Lecture slides
Lecture
Wed Jan 12 Feature engineering Lecture note
Lecture slides
Lecture
Mon Jan 17 No class Martin Luther King, Jr. Day
Wed Jan 19 Model selection, development, and training Lecture note
Lecture slides
Lecture
Mon Jan 24 Offline evaluation Lecture note
Lecture slides
Lecture
Wed Jan 26 Model evaluation
    Tutorial by Goku Mohandas (MadeWithML)
    RecList by our very own Chloe He
Goku's ML tutorial
RecList
Tutorial
Mon Jan 31 Deployment Lecture note
Lecture slides
Lecture
Wed Feb 2 Deployment tutorials
    How to evaluate MLOps tools by Hamel Husain
    Deploy models with Ray Serve by Simon Mo (Anyscale)
Hamel's slides
Hamel's video
Ray tutorials
Tutorial
Mon Feb 7 Diagnosis of ML system failures & data distribution shifts & monitoring Lecture note
Lecture slides
Lecture
Wed Feb 9 Monitoring & Continual Learning
Data Distribution Shifts on Streaming Data by Shreya Shankar
Kinbert's slides
Shreya's slides
Guest Lecture
Mon Feb 14 Model Deployment @ Stitch Fix by Stefan Krawczyk
Experiment tracking & versioning with Weights & Biases by Lavanya Shukla
Stefan's slides
Lavanya's slides
Case Study + Tutorial
Wed Feb 16 Monitoring Tutorial
    WhyLogs tutorials by Alessya Visnjic
    Evidently tutorials by Emeli Dral
Evidently notebook
WhyLogs notebook
WhyLogs' slides on telemetry for ML
Tutorial
Mon Feb 21 No class Presidents' Day
Wed Feb 23 Deploying time series forecasting and graph neural networks by Kyle Kranen
ML beyond accuracy: Fairness, Security, Governance by Sara Hooker
Sara's slides Guest Lecture
Mon Feb 28 ML Infrastructure and Platform Lecture slides
Lecture
Wed Mar 2 Final project discussion Workshop
Mon Mar 7 Integrating ML into business
Grace Isford (Lux Capital): How to pitch
Nnamdi Iregbulem (Lightspeed): Go to market
Astasia Myers (Quiet): Business values of AI
Guest Lecture
Wed Mar 9 Final project demo day Recordings of 24 demos can be found on YouTube
Join us!
Demo day