CS 189/289A: Intro to Machine Learning
UC Berkeley, Fall 2025
Ed Gradescope Additional Accommodations Office Hours Queue
Lectures Playlist
Welcome to Week 1 of CS 189/289A!
Lectures will be broadcast at this link
Schedule
Week 1
- Wed Aug 27
- First Day of Classes
- Thu Aug 28
- Lecture 1 Introduction + ML Problem Framing
- Fri Aug 29
Week 2
- Mon Sep 1
- Tue Sep 2
- Lecture 2 Working with Data
- Wed Sep 3
- Discussion 1 Introduction to ML
- Thu Sep 4
- Lecture 3 ML Mechanics (Techniques)
- Fri Sep 5
- Homework 1 Intro to ML
- Homework 1 Written Math Refresher
Week 3
- Mon Sep 8
- Tue Sep 9
- Lecture 4 Probability Prereq + KMeans + EM
- Wed Sep 10
- Discussion 2 Working with Data & ML Techniques
- Thu Sep 11
- Lecture 5 MSE/MAE + Linear Regression + Regression to Classification
Week 4
- Mon Sep 15
- Tue Sep 16
- Lecture 6 Linear Regression MLE
- Wed Sep 17
- Discussion 3 Probability & KMeans & Linear Regression
- Thu Sep 18
- Lecture 7 Linear Regression
- Fri Sep 19
- Homework 1 - Part 1 and Homework 1 Written Due
Week 5
- Mon Sep 22
- Tue Sep 23
- Lecture 8 MLE + Logistic Regression (1)
- Wed Sep 24
- Discussion 4 Linear Regression & MLE
- Thu Sep 25
- Lecture 9 MLE + Logistic Regression (2)
- Fri Sep 26
- Homework 2 Chatbot Arena
- Homework 1 - Part 2 due
Week 6
- Mon Sep 29
- Tue Sep 30
- Lecture 10 Gradient Descent (1)
- Wed Oct 1
- Discussion 5 Logistic Regression & MLE
- Thu Oct 2
- Lecture 11 Gradient Descent (2)
- Fri Oct 3
- Homework 2 Part 1 due
Week 7
- Mon Oct 6
- Tue Oct 7
- Lecture 12 Neural Networks (1): Build Non-linearity, Architecture, Activation Functions
- Wed Oct 8
- Discussion 6 Gradient Descent
- Thu Oct 9
- Lecture 13
- Fri Oct 10
Week 8
- Mon Oct 13
- Tue Oct 14
- Lecture 14 Neural Networks (3): Backpropagation
- Wed Oct 15
- Discussion 7 Neural Networks Basics
- Thu Oct 16
- Lecture 15 Neural Networks (4): Batch Normalization, Initialization, Regularization
- Fri Oct 17
- Homework 3 Backprop and Neural Nets
- Homework 2 Part 2 due
Week 9
- Mon Oct 20
- Tue Oct 21
- Midterm Exam Midterm (7:00 - 9:00pm)
- Wed Oct 22
- Discussion 8 Neural Networks & Backpropagation
- Thu Oct 23
- Lecture 16 Guest Lecture - Efros - NN Fun Lecture
- Fri Oct 24
- Homework 3 - Part 1 due
Week 10
- Mon Oct 27
- Tue Oct 28
- Lecture 17 Architectures: CNN
- Wed Oct 29
- Discussion 9 Guest Lecture Follow-up & CNN Intro
- Thu Oct 30
- Lecture 18 Architectures: RNN
- Fri Oct 31
- Halloween
Week 11
- Mon Nov 3
- Tue Nov 4
- Lecture 19 Transformers
- Wed Nov 5
- Discussion 10 CNN & RNN Architectures
- Thu Nov 6
- Lecture 20 Generative Models - NLP (LLM) Part 1
- Fri Nov 7
- Homework 4 CNNs and Transformers
- Homework 3 Part 2 due
Week 12
- Mon Nov 10
- Tue Nov 11
- Veterans Day No Lecture
- Wed Nov 12
- Discussion 11 Transformers & LLMs
- Thu Nov 13
- Lecture 21 Generative Models - NLP (LLM) Part 2
- Fri Nov 14
- Homework 4 - Part 1
Week 13
- Mon Nov 17
- Tue Nov 18
- Lecture 22 Dimensionality Reduction (PCA)
- Wed Nov 19
- Discussion 12 Generative Models & NLP
- Thu Nov 20
- Lecture 23
- Fri Nov 21
Week 14
- Mon Nov 24
- Tue Nov 25
- Lecture 24 Auto-encoder + GAN Basics (2)
- Wed Nov 26
- Discussion 13 PCA & Auto-encoders
- Thu Nov 27
- Thanksgiving No Lecture
- Fri Nov 28
- Homework 5 Pre-training + instruction-tuning
- Homework 4 - Part 2 due
Week 15
- Mon Dec 1
- Tue Dec 2
- Lecture 25 Guest Lecture - Sergey
- Wed Dec 3
- Discussion 14 GANs & Course Review
- Thu Dec 4
- Lecture 26 Course Closing
- Fri Dec 5
Week 16 - RRR Week
- Mon Dec 8
- Finals Week
- Tue Dec 9
- Study Day
- Wed Dec 10
- Study Day
- Thu Dec 11
- Study Day
- Fri Dec 12
- Homework 5 DUE
Week 17 - Finals Week
- Tue Dec 16
- Final Exam Final (8:00-11:00 AM)