MIT 6.S191: Introduction to Deep Learning is an introductory course offered formally at MIT and open-sourced on the course website. The class consists of a series of foundation lectures on the fundamentals of neural networks, its applications to sequence modeling, computer vision, generative models, and reinforcement learning.
MIT 6.S191: MIT’s official introductory course on deep learning algorithms and their applications
MIT 6.S191 equips the students with the practical skills necessary to go out and implement their own deep learning models, to apply what they got out of this course to the questions that excite and inspire them. The team designed two TensorFlow based software labs, focusing on music generation with recurrent neural networks and pneumothorax detection in medical images, to complement the course lectures. The TensorFlow labs give students an opportunity to apply the fundamentals to two interesting, relevant problems and to build and refine their TensorFlow skills.

“A baby learns to crawl, walk and then run. we are in the crawling stage when it comes to applying Artificial Intelligence.”
-Dave Waters