The class starts by providing a fundamental grounding in combinatorics, and then quickly moves into the basics of probability theory. We will then cover many essential concepts in probability theory, including particular probability distributions, properties of probabilities, and mathematical tools for analyzing probabilities. Finally, the last third of the class will focus on data analysis and Machine Learning as a means for seeing direct applications of probability in this exciting and quickly growing subfield of computer science.
Lecture content is subject to change by the management at any time.
1

#  Weekday  Date  Topic  Notes 

Week 1  
3

1  Wednesday  Sept 27  Counting  
4

2  Friday  Sept 29  Combinatorics  PSet 1 out 
Week 2  
5

3  Monday  Oct 2  What is Probability?  
7

4  Wednesday  Oct 4  Conditional Probability and Bayes  
8

5  Friday  Oct 6  Independence  
Week 3  
9

6  Monday  Oct 9  Random Variables and Expectation  PSet 1 in / PSet 2 out 
11

7  Wednesday  Oct 11  Variance Bernoulli Binomial  
12

8  Friday  Oct 13  Poisson  
Week 4  
13

9  Monday  Oct 16  Continuous Random Variables  
15

10  Wednesday  Oct 18  Normal Distribution  PSet 2 in / PSet 3 out 
16

11  Friday  Oct 20  Joint Distributions  
Week 5  
17

12  Monday  Oct 23  Inference  
19

13  Wednesday  Oct 25  Variable Inference  
14  Friday  Oct 27  General Inference  PSet 3 in  
Week 6  
  Monday  Oct 30  No Class  Midterm, 7pm  9pm  
16  Wednesday  Nov 1  Beta  PSet 4 out  
17  Friday  Nov 3  Adding Random Variables  
Week 7  
18  Monday  Nov 6  Central Limit Theorem  Challenge out  
19  Wednesday  Nov 8  Bootstraping and PValues  
20  Friday  Nov 10  Algorithmic Analysis  PSet 4 in / PSet 5 out  
Week 8  
21  Monday  Nov 13  M.L.E.  
22  Wednesday  Nov 15  M.A.P.  
23  Friday  Nov 17  Naive Bayes  PSet 5 in  
Thanksgiving Break  
Week 9  
24  Monday  Nov 27  Logistic Regression  PSet 6 out  
25  Wednesday  Nov 29  Deep Learning  
26  Friday  Dec 1  Fairness  
Week 10  
27  Monday  Dec 4  Advanced Probability  
28  Wednesday  Dec 6  DallE and GPT  PSet 6 in, Challenge in  
29  Friday  Dec 8  No Class  Final: Wed, Dec 13th, 7pm  10pm 
This quarter we are writing a Course Reader for CS109 which is free and written for the course. You can optionally read from Sheldon Ross, A First Course in Probability (10th Ed.), Prentice Hall, 2018. The corresponding readings can be found Win 21 schedule. The textbook's 8th and 9th editions have the same readings and section headers.