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.

Registration

Registration for MIT students is now open! Click here to register! If you are not an MIT student but would like to receive course updates and lecture material please sign up for our mailing list.

Questions?

Reach out to introtodeeplearning-staff@mit.edu

To view archived versions of this website from past years please click here.

6.S191 Team

Alexander

Alexander Amini

Lead Organizer

Ava

Ava Soleimany

Lead Organizer

Harini

Harini Suresh

Co-Chair

Lex

Lex Fridman

Co-Chair

Unknown

Want to be part of this course?


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

If you are interested, please contact introtodeeplearning-staff@mit.edu

Sponsors

IBM Watson


NVIDIA


microsoft


Google Brain