CS109

Course Resources
Syllabus Schedule Honor Code Office Hours Course Reader Python Review Latex Cheat Sheet Lecture Videos AIWG Student Guide
Challenge
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
Section
Section Signup Form Section 1 Section 2 Section 3 Section 4
PEP
Midterm

Schedule

Lecture 22: Deep Learning

May 18, 2026
NVIDIA Auditorium, 1:30pm

Lecture Materials

Learning Goals

Learn about feed forward deep learning networks and the theory behind back propagation.