CS109
Course Resources
Syllabus
Schedule
Honor Code
Office Hours
Course Reader
Python Review
Latex Cheat Sheet
Lecture Videos
AIWG Student Guide
Midterm 1
Problem Sets
1. Core Probability
2. Discrete Random Variables
3. Continuous Random Variables
4. Probabilistic Models
Lecture
1. Welcome
2. Conditioning and Bayes
3. Independence
4. Counting
5. Binomial
6. Moments
7. Poisson
8. Continuous
9. Gaussian
10. Probabilistic Models
11. Inference
12. General Inference
13. Multinomial
14. Beta
15. Central Limit Theorem
16. Sampling & Bootstrapping
17. Algorithm Analysis
18. Information Theory
19. Maximum Likelihood Estimation
Schedule
Section 8
May 26th, 2026
This week is practice with a few CS109 concepts.
Section Materials
Section Handout
Section Soln