CS109

Course Resources
Syllabus Schedule Honor Code Office Hours Course Reader Python Review Latex Cheat Sheet Lecture Videos AIWG Student Guide
Challenge Midterm
Problem Sets
1. Core Probability 2. Discrete Random Variables 3. Continuous Random Variables 4. Probabilistic Models 5. Uncertainty Theory 6. Information Theory + MLE
Music Voting View Playlist
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. Algorithm Analysis 17. Information Theory 18. Sampling & Bootstrapping
Check Lecture Attendance
Section
Section 1 Section 2 Section 3 Section 4 Section 5 Section 6
Section Reassign Form Times and Locations
PEP
Midterm

Schedule

Lecture 14: Beta

Feb 6th, 2026
Hewlett 200, 3p

Lecture Materials

Lecture Questions

Lecture Solutions

Learning Goals

Know how to think about uncertainty in probabilities