This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application.

Interested in the class? Here are some things you could do:

  1. Register an account on the site to stay up-to-date. The material for the course is free and open to the everyone.
  2. Join our Slack channel (deep-mit.slack.com). There are two ways:
    (a) if you have an mit.edu email, join here
    (b) get an invite by clicking here.
  3. Watch the lectures and guest talks (from 2017 and 2018). We'll make videos available a few days after the lecture is given.
  4. If you have questions, check out the FAQ Google Doc.
  5. Interact with Lex on Twitter, LinkedIn, Instagram, Facebook, or subscribe on YouTube.
  6. Check out MIT 6.S099: Artificial General Intelligence.

Course Information:

  • Time/Dates: Every day, 7pm, Jan 8 - Jan 19
  • Duration: 60-90 minutes
  • Location: MIT, 54-100 (location details) with some exceptions.
  • Instructor: Lex Fridman
  • Contact: deepcars@mit.edu

2018 Schedule of Lectures and Talks

Most (but not all) lectures and talks will be at 7pm in Room 54-100. See below for exact time and location.
Lecture 1
Deep Learning
[ Slides ] - [ Lecture Video ]
Lecture 2
Self-Driving Cars
[ Slides ] - [ Lecture Video ]
Lecture 3
Deep Reinforcement Learning
[ Slides ] - [ Lecture Video ]
Lecture 4
Computer Vision
[ Slides ] - [ Lecture Video ]
Lecture 5
Deep Learning for Human Sensing
[ Slides ] - [ Lecture Video ]
Guest Talk
Sacha Arnoud
Director of Engineering, Waymo
Guest Talk
Emilio Frazzoli
CTO, nuTonomy. Previously: Professor, MIT.
Guest Talk
Sterling Anderson
Co-Founder, Aurora. Previously: Director, Tesla Autopilot.


MIT 6.S094: Deep Learning for Self-Driving Cars is a course on a cutting-edge research area. The research group behind this course includes:

2017 Lecture Slides and Videos:

  • Lecture 1: Introduction to Deep Learning and Self-Driving Cars
    [ Slides ] - [ Lecture Video ]
  • Lecture 2: Deep Reinforcement Learning for Motion Planning
    [ Slides ] - [ Lecture Video ]
  • Lecture 3: Convolutional Neural Networks for End-to-End Learning of the Driving Task
    [ Slides ] - [ Lecture Video ]
  • Lecture 4: Recurrent Neural Networks for Steering through Time
    [ Slides ] - [ Lecture Video ]
  • Lecture 5: Deep Learning for Human-Centered Semi-Autonomous Vehicles
    [ Slides ] - [ Lecture Video ]
  • Extra: MIT Sloan: Intro to Machine Learning (in 360/VR)
    [ Slides ] - [ Lecture Video ]

2017 Guest Talks:

Technology, Policy and Vehicle Safety in the Age of AI
Professor, Stanford
Past, Present, and Future of Motion Planning in a Complex World
Professor, MIT
From Research to Reality: Testing Self-Driving Cars on Public Roads
CEO, nuTonomy and Research Scientist, MIT
Self-Driving Vehicles, SLAM, and Deep Learning
Professor, MIT
We Only Adopt What We Trust: Policy and the Business of Autonomy
White House Presidential Innovation Fellow, Office of Science and Technology Policy

Thank You

Support for this course was genorously provided by the companies whose logos are shown below. And none of it would be possible without the great community of bright young minds at MIT and beyond.