Schedule (Tentative)

Week

Topic

Assignment

Readings

Week 1: 9/1 & 9/4

What is AI?

Agents and Environments

Homework 1 (due 9/3)

Required: Jordan (2019)

Reference: Russell & Norvig Chapter 2

Week 2: 9/8 & 9/11

Search Problems

Uninformed search

Homework 2 (due 9/14)

ANY: Shadow Self

Reference: Russell & Norvig Chapter 3

Week 3: 9/15 & 9/18

Informed search

Adversarial search

Homework 3 (due 9/21)

Required: Mitchell Chapter 8-9

Reference: Russell & Norvig Chapter 5

Reference: Minimax recap

Week 4: 9/22 & 9/25

Reinforcement learning

Homework 4 (due 9/28)

Required: ANY, p. 28-52

Reference: RL recap

Reference: Flip side of RL

Week 5: 9/29 & 10/2

Regression

Cat/dog dataset

Required: ANY, p. 53-70

Reference: Jurafsky & Martin Chapter 4

Reference: Regression in more depth

Week 6: 10/5 & 10/7

Midterm 1

Neural networks

Homework 5 (due 10/19)

Reference: Jurafsky & Martin Chapter 6

Week 7: 10/14

Fall Break

Required: ANY, p. 71-101

Week 8: 10/20 & 10/23

Gradient Descent

Gradient Descent game

Representing Images and Text

Homework 6 (due 11/2)

Required: ANY, p. 101-120

Reference: Jurafsky & Martin Chapter 6

Reference: Gradient descent video

Week 9: 10/30

Training neural networks

Required: ANY, p. 121-169

Week 10: 11/3 & 11/6

Language models

Transformers

Required: ANY, p. 170-215

Reference: Jurafsky & Martin Chapter 8

Reference: GPT-2 blog post

Week 11: 11/10 & 11/13

Midterm 2

Using Transformers

Homework 7 (due 11/16)

Recommended: Chiang (2023)

Reference: Jurafsky & Martin Chapter 9

Week 12: 11/17 & 11/20

RLHF

Evaluating AI

Homework 8 (due 11/23)

Required: ANY, p. 216-235

Reference: Jurafsky & Martin Chapter 9

Reference: Arvind Narayanan's talk on 21 definitions of fairness

Week 13: 11/24

AI over time

Required: Jensen et al. (2025)

Week 14: 12/1 & 12/4

Societal impacts of AI

Required: Chiang (2026)

Week 15: 12/8

Project presentations

Final project description