Course Information

Class Meetings

The whole class will meet on 5th January (4.15pm-5.30pm, Gates 120) and 9th Feb (4.15-5.30pm, Gates 120). Final project presentations are scheduled for Thursday, March 17, 1:30pm-3:00pm. The instructor and TAs will have regularly scheduled smaller meetings with each project team.

In case you have questions about the lecture notes or programming assignment, we will also have office hours from 9-10am on Friday, Jan 7th and 9-10am on Monday, Jan 10th in Gates 110.

This class will not have regularly scheduled lectures.

Teaching Staff

Instructor: Andrew Ng
Office: Gates 156
Phone: (650)725-2593

TA: Quoc Le
Office: Gates 110
Phone: (650)723-4310

TA: Morgan Quigley
Office: Gates 112
Phone: (650)723-4310

Thanks also to Jiquan Ngiam, Adam Coates, Andrew Maas, Andrew Saxe, and Richard Socher.

Course Overview

This is a project course, with only one introductory homework and no lectures. We will spend the quarter working on different research projects related to unsupervised deep learning.

Specifically, students will work in teams on different deep learning algorithms. The goal is to have each team do a publishable piece of research.

Because it is challenging to work on algorithmic machine learning, we will be able to work with only a small number of students, and enrollment will be limited. You can find details about enrollment requirements on the Handouts and enrollment information page.


Important dates


CS294A can be used to satisfy the CS or CSE undergraduate program's senior project requirement. In addition, CS294W can be used to satisfy the WIM requirement in the undergraduate CS or CSE program. Please sign up for either CS294A or for CS294W, and not for both. See the CS294W page for more information about satisfying the WIM requirement with CS294W.

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