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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

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