Schedule & syllabus

The lecture slides, notes, tutorials, and assignments will be posted online here as the course progresses.
Lecture times are 2:30-3:50pm PST. All deadlines are at 11:59pm PST.

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

Date Description Materials Events
Mon Jan 11 Understanding machine learning production Note
Slides
Lecture
Wed Jan 13 Intro to machine learning systems design Note
Slides
Lecture
Mon Jan 18 No class Martin Luther King, Jr. Day
Wed Jan 20 Data engineering Slides
Note
Lecture
Mon Jan 25 Model development Slides
Note
Lecture
Wed Jan 27 PyTorch & distributed training
    Tutorial by Shreya Shankar and Karan Goel
Slides - PyTorch (Shreya)
Slides - scaling (Karan)
Lecture + Tutorial
Mon Feb 1 Model evaluation Slides
Lecture
Wed Feb 3 Experiment tracking and versioning
    Weights & Biases tutorial by Lavanya Shukla
    DVC tutorial by DVC team
Slides Lecture + Tutorial
Mon Feb 8 Deployment Slides
Lecture
Wed Feb 10 Deployment tutorials
    Guest lecture by Daniel Bourke
Slides
Video
Code
Tutorial
Mon Feb 15 No class Presidents' Day
Wed Feb 17 TinyML
    Guest lecture by Pete Warden
Slides Lecture
Mon Feb 22 Scaling ML models in production: case studies with Uber and Ludwig
    Guest lecture by Piero Molino
Slides
Lecture
Wed Feb 24 Model Deployment Beyond Test Set Accuracy by Sara Hooker
ML in production by Andrej Karpathy
Slides - Sara Lecture
Mon Mar 1 Monitoring and maintenance Lecture + Tutorial
Wed Mar 3 Infrastructure Lecture
Mon Mar 8 Integrating ML into business
    Guest lecture by Saam Motamedi
Lecture
Wed Mar 10 Final project discussion Workshop
Mon Mar 15 Future of ML systems
Panel:
  1. Christopher RĂ©
  2. Neil Lawrence
  3. Han Xiao
  4. TBD
Panel
Wed Mar 17 Final project demo day Demo day