CS 21SI: AI for Social Good

Spring 2021

As AI becomes more ubiquitous, so do its opportunities to positively affect society. At the same time, so increase ways that AI can be used to hurt and disrupt people's lives. "AI for Social Good" is a 2-unit course aimed at training the next generation of socially-conscientious AI engineers.

Syllabus

Intro to Machine Learning

Week 1: Linear Models & Logistic Regression, Homework* 1
Resources: Class Exercises Solutions

Week 2: Invited Talk** from Mehran Sahami

Deep Learning I

Week 3: Neural Networks & Gradient Descent, Homework 2
Resources: Class Exercises Solutions

Week 4: Invited Talk from Elizabeth Adams

Deep Learning II

Week 5: Activation Functions & Regularization, Homework 3

Week 6: Invited Talk from Stefano Ermon

Computer Vision

Week 7: Convolutional Neural Networks, Homework 4

Week 8: Invited Talk from Christopher Brown

Natural Language Processing

Week 9: Recurrent Neural Networks & Transformers, Homework 5

Week 10: Invited Talk from Xavier Boix
*Students are required to do at least 4 of the 5 homeworks (each homework is a very short Colab notebook; see previous year's syllabus for examples)
**Students are required to attend at least 4 of the 5 invited talks

Speakers From:

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Apply for the Course

We will reach out before the quarter starts with an enrollment code for AXESS.

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