CS 189/289A: Intro to Machine Learning
UC Berkeley, Fall 2026
Ed Gradescope Office Hours Queue Content Repository
- Our course staff email is cs189-instructors@berkeley.edu. This email is monitored by the instructors, the head TAs, and a few lead TAs.
Welcome to Week 1 of CS 189/289A!
Lectures will be broadcast at this link.
Please note that the size of this course is not expanding, and we cannot predict whether you will get off the waitlist.
Schedule
Week 1 (Current Week)
- Mon Aug 24
- Tue Aug 25
- No Lecture No Lecture
- No Discussion No Discussion
- Wed Aug 26
- Thu Aug 27
- Lecture 1 Introduction + ML Problem Framing
- Fri Aug 28
Week 2
- Mon Aug 31
- Tue Sep 1
- Lecture 2 Data Tools + K-Means and KNN
- Discussion 1 Math Refresher (Linear Algebra)
- Wed Sep 2
- Thu Sep 3
- Lecture 3 Math Refresher + Probability + Linear Algebra
- Fri Sep 4
- Homework 1
Week 3
- Mon Sep 7
- Labor Day - Holiday
- Tue Sep 8
- Lecture 4 Density Estimation
- Discussion 2 Math Refresher + Probability + Density Estimation
- Wed Sep 9
- Thu Sep 10
- Lecture 5 Gaussian Mixture Models
- Fri Sep 11
Week 4
- Mon Sep 14
- Tue Sep 15
- Lecture 6 Linear Regression
- Discussion 3 Linear Regression + MLE
- Wed Sep 16
- Thu Sep 17
- Lecture 7 Bias-Variance Trade-off + Regularization
- Fri Sep 18
- Homework 1 Part 1 due
Week 5
- Mon Sep 21
- Tue Sep 22
- Lecture 8 Logistic Regression (1)
- Discussion 4 Logistic Regression + Regularization + Bias/Variance
- Wed Sep 23
- Thu Sep 24
- Lecture 9 Logistic Regression (2)
- Fri Sep 25
- Homework 2
- Homework 1 Part 2 due
Week 6
- Mon Sep 28
- Tue Sep 29
- Lecture 10 Gradient Descent (1)
- Discussion 5 Gradient Descent
- Wed Sep 30
- Thu Oct 1
- Lecture 11 Gradient Descent (2)
- Fri Oct 2
Week 7
- Mon Oct 5
- Tue Oct 6
- Lecture 12 Neural Networks (1)
- Discussion 6 Neural Networks
- Wed Oct 7
- Thu Oct 8
- Lecture 13 Neural Networks (2): Backpropagation
- Fri Oct 9
- Homework 2 Part 1 due
Week 8
- Mon Oct 12
- Tue Oct 13
- Lecture 14 Neural Networks (3)
- Discussion 7 Neural Network Regularization
- Wed Oct 14
- Thu Oct 15
- Lecture 15 Neural Networks (4)
- Fri Oct 16
- Homework 3
- Homework 2 Part 2 due
Week 9
- Mon Oct 19
- Tue Oct 20
- No Lecture No Lecture
- No Discussion No Discussion
- Midterm Exam Midterm (time TBD)
- Wed Oct 21
- Thu Oct 22
- Lecture 16 Neural Networks (5) + Architectures: CNN
- Fri Oct 23
Week 10
- Mon Oct 26
- Tue Oct 27
- Lecture 17 Architectures: CNN
- Discussion 8 CNNs
- Wed Oct 28
- Thu Oct 29
- Lecture 18 Transformers
- Fri Oct 30
- Homework 3 Part 1 due
Week 11
- Mon Nov 2
- Tue Nov 3
- Lecture 19 LLMs (1)
- Discussion 9 Transformers
- Wed Nov 4
- Thu Nov 5
- Lecture 20 LLMs (2)
- Fri Nov 6
- Homework 4
- Homework 3 Part 2 due
Week 12
- Mon Nov 9
- Tue Nov 10
- Lecture 21 Attention Methods
- Discussion 10 LLMs
- Wed Nov 11
- Veterans Day - Holiday
- Thu Nov 12
- Lecture 22 MDP, Reinforcement Learning (1)
- Fri Nov 13
Week 13
- Mon Nov 16
- Tue Nov 17
- Lecture 23 Reinforcement Learning (2)
- Discussion 11 Reinforcement Learning
- Wed Nov 18
- Thu Nov 19
- Lecture 24 Guest Lecture: TBD
- Fri Nov 20
- Homework 4 Part 1 due
Week 14
- Mon Nov 23
- Tue Nov 24
- Lecture 25 Post-training
- Discussion 12 Post-training
- Wed Nov 25
- Thanksgiving - Holiday
- Thu Nov 26
- No Lecture No Lecture
- Fri Nov 27
- Homework 5
- Homework 4 Part 2 due
Week 15
Week 16
- Mon Dec 7
- Tue Dec 8
- Wed Dec 9
- Thu Dec 10
- Fri Dec 11
- Homework 5 Part 2 due
Week 17 - Finals Week
- Mon Dec 14
- Tue Dec 15
- Wed Dec 16
- Thu Dec 17
- Final Exam Final (11:30 AM - 2:30 PM, cumulative)
- Fri Dec 18