Description

An efficient and high-intensity bootcamp designed to teach you the fundamentals of deep learning as quickly as possible!

MIT's introductory program on deep learning methods with applications to natural language processing, computer vision, biology, and more! Students will gain foundational knowledge of deep learning algorithms, practical experience in building neural networks, and understanding of cutting-edge topics including large language models and generative AI. Program concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. Listeners are welcome!

Time and Location

MIT 6.S191
Mon Jan 8 - Fri Jan 12, 2024
3pm - 6pm EST Everyday

3:00pm-3:55pm: Lecture Part 1
4:00pm-4:55pm: Lecture Part 2
5:00pm-6:00pm: Software Labs

MIT Room 32-123
New competitions & prizes!

Schedule

New 2024 lectures, slides, and labs!
Taught in-person at MIT — open-sourced to the world.


Intro to Deep Learning
Lecture 1
Jan. 8, 2024

[Slides] [Video] coming soon!

Deep Sequence Modeling
Lecture 2
Jan. 8, 2024

[Slides] [Video] coming soon!

Intro to TensorFlow;
Music Generation
Software Lab 1

[Code]

Deep Computer Vision
Lecture 3
Jan. 9, 2024

[Slides] [Video] coming soon!

Deep Generative Modeling
Lecture 4
Jan. 9, 2024

[Slides] [Video] coming soon!

Facial Detection Systems
Software Lab 2

[Paper] [Code]

Deep Reinforcement Learning
Lecture 5
Jan. 10, 2024

[Slides] [Video] coming soon!

New Frontiers
Lecture 6
Jan. 10, 2024

[Slides] [Video] coming soon!

Large Language Models
Software Lab 3

[Code] coming soon!

Generative AI for Media
Lecture 7
Jan. 11, 2024

[Info] [Slides] [Video] coming soon!

Stories from Models in the Wild
Lecture 8
Jan 11, 2024

[Info] [Slides] [Video] coming soon!

Final Project
Work on final projects

Final Project
Work on final projects
Jan 12, 2024
Project Presentations
Pitch your ideas!
Jan 12, 2024
Awards Ceremony
Final awards and celebration!

Frequently Asked Questions

For any other questions please reach out to the staff at introtodeeplearning-staff@mit.edu.

All listeners are welcome to attend!
In 2024, 6.S191 will be offered as a for-credit 6-unit MIT course and graded P/D/F based on completion of project proposal assignment.
Registration opens on Dec 1 at 9am. If you are a current MIT student please register here after registration opens. You can specify if you want to take the course for credit or as a listener there.

In addition, everyone interested in taking the course (MIT or not; and in-person or not), should also register on the internal registration to receive updates.

After the MIT program, the content will be open-sourced to the world. Again, please sign up for the internal registration to receive updates when this occurs.

We are expecting very elementary knowledge of linear algebra and calculus. How to multiply matrices, take derivatives and apply the chain rule. Familiarity in Python is a big plus as well. The program will be beginner friendly since we have many registered students from outside of computer science.

If you would like to receive related updates and lecture materials please subscribe to our YouTube channel and sign up for our mailing list.

All materials are open-sourced to the world for free and are copyrighted under the MIT license. If you are an instructor and would like to use any materials from this program (slides, labs, code), you must add the following reference to each slide:

© Alexander Amini and Ava Amini
MIT Introduction to Deep Learning
IntroToDeepLearning.com

All materials are copyrighted and licensed under the MIT license. If you are an instructor and would like to use any materials from this program (slides, labs, code), you must add the following reference to each slide:

© Alexander Amini and Ava Amini
MIT 6.S191: Introduction to Deep Learning
IntroToDeepLearning.com

If you are an MIT student, postdoc, faculty, or affiliate and would like to become involved with this program please email introtodeeplearning-staff@mit.edu. We are always accepting new applications to join the program staff.

This class would not be possible without our amazing sponsors and has been sponsored by Google, IBM, NVIDIA, Microsoft, Amazon, LambdaLabs, Tencent AI, Ernst and Young, and Onepanel. If you are interested in becoming involved in this program as a sponsor please contact us at introtodeeplearning-staff@mit.edu.

To view archived versions of this website from past years please click here for 2023, 2022, 2021, 2020, 2019, 2018, and 2017.

Team

amini

Alexander Amini

Lead Instructor
Organizer

avaamini

Ava Amini

Lead Instructor
Organizer

sadhana

Sadhana Lolla

Instructor
Lead TA

Teaching Assistants

shornaalam

Shorna Alam

anirudhvaliveru

Anirudh Valiveru

divyanori

Divya Nori

alexlavaee

Alex Lavaee

shreyaravikumar

Shreya Ravikumar

franklinwang

Franklin Wang

evaxie

Eva Xie

We are always accepting new applications to join the program staff. If you are interested in becoming a TA, please contact introtodeeplearning-staff@mit.edu

Sponsors

This program and delivery would not be possible without our amazing sponsors! If you are interested in becoming involved in this program as a sponsor please contact us at introtodeeplearning-staff@mit.edu