Training the model is just one part of shipping a deep learning project. This course teaches full stack production deep learning:

  • Formulating the problem and estimating project cost
  • Finding, cleaning, labeling, and augmenting data
  • Picking the right framework and compute infrastructure
  • Troubleshooting training and ensuring reproducibility
  • Deploying the model at scale

Students will work on deploying a deep learning system into production, learn how to prepare for interviews, and test their knowledge via an optional written exam. The FSDL community also offers benefits of an active peer network comprising top deep learning practitioners - learn, deploy, and collaborate with the best.

Meet Our Instructors

Pieter Abbeel

Co-Founder, President, and Chief Scientist of Covariant.AI, Professor at UC Berkeley

Sergey Karayev

Co-Founder of Gradescope, Head of AI for STEM at Turnitin

Josh Tobin

Research Scientist at OpenAI


Guest Speakers

Franziska Bell, Uber

Fran leads Applied Machine Learning, Forecasting, and Natural Language Understanding platform data science teams at Uber.

Franziska Bell, Uber

Lukas Biewald

Founder and CEO of Weights & Biases (ML services company). Previously founded and led FigureEight (largest ML data annotation company).

Lukas Biewald, Weights & Biases

Xavier Amatriain

Co-founder and CTO at Curai. Previously: VP of Engineering at Quora, led Algorithms Engineering at Netflix.

Xavier Amatriain, Curai

Chip Huyen

Chip created the TensorFlow for Deep Learning Research course at Stanford University. She currently works on the AI Applications team at Nvidia.

Chip Huyen, Nvidia

Workshop Fees

We strongly encourage members of underrepresented groups to apply. is generously sponsoring a scholarship program - details are available in the application.





Live-Stream Attendee
(Outside of the US)


Frequently Asked Questions

Our course is aimed at people who already know the basics and want experience with the full stack. We expect you to have:

  • At least one year experience programming in Python.
  • At least one deep learning course (can be online).
  • Experience with code versioning, Unix environments, and software engineering.

We will not review the fundamentals of deep learning (gradient descent, backpropagation, convolutional neural networks, recurrent neural networks, etc), so you should review these materials in advance of the bootcamp if you are rusty.

Please feel free to reach out to us with any questions at!