Course Description

An introductory course on deep learning methods with applications to machine translation, image recognition, game playing, image generation and more. A collaborative course incorporating labs in TensorFlow and peer brainstorming along with lectures. Course concludes with project proposals with feedback from staff and panel of industry sponsors.

Recommended prerequisites: one of 6.036, 6.034, 6.008, 6.867, 6.864, 6.804, 15.075, IDS.301, 6.047, 6.041, 6.438 or equivalent experience

Time and Location

Jan 29 - Feb 2
10:30am-1:30pm, Room 32-123

10:30a-11:15pm: Lecture Part 1
11:15a-12:00pm: Lecture Part 2
12:00pm-12:30pm: Coffee Break
12:30pm-1:30pm: Lab (Hands-On TensorFlow Tutorials)

Grading Policy

P/F based on completion of project proposal assignment

Project Proposals

Project proposals will be 1-minute pitches of a novel deep learning algorithm, application, open-source contribution, plan to create an interesting dataset, or other contributions. Sponsors will judge and select top projects as award winners. Alternative to project proposal is to submit a 1-page review of an interesting deep learning paper.


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6.S191 Team


Alexander Amini

Lead Organizer


Ava Soleimany

Lead Organizer


Harini Suresh



Lex Fridman



Want to be part of this course?

We are looking for more TA's and administrative individuals to help with the course!

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IBM Watson



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