This course introduces deep learning in computer science. (Image is in the public domain. Courtesy of Markus Spiske.)
Instructor(s)
Alexander Amini
Ava Soleimany
MIT Course Number
6.S191
As Taught In
January IAP 2020
Level
Undergraduate
Course Description
Course Features
Course Description
This is MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course 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), and we'll try to explain everything else along the way! Experience in Python is helpful but not necessary.