# CSE 312: Foundations of Computing II, Summer 2020

• [6/21] Welcome to CSE 312! The below is a tentative schedule that is subject to change, make sure to check it for the most up-to-date plan for the course!

## Schedule

Week 1
Topic
Materials
Assignments
Week 1
Lecture 1
(Mon, Jun 22)
0.3 Sum and Product Notation
1.1 So You Think You Can Count?
Recitation 1
(Tues, Jun 23)
LaTeX Tutorial and Practice
Lecture 2
(Wed, Jun 24)
1.2 More Counting
Section 1
(Thu, Jun 25)
9.1Python Tutorial
9.2Probability via Simulation [PSet1 Coding]
Syllabus cc Due 11:45AM
Lecture 3
(Fri, Jun 26)
2.1 Discrete Probability
2.2 Conditional Probability
Week 2
Lecture 4
(Mon, Jun 29)
2.3 Independence
3.1 Discrete Random Variables Basics
Recitation 2
(Tues, Jun 30)
More Counting and Probability
Lecture 5
(Wed, Jul 1)
3.2 More on Expectation
3.3 Variance
Section 2
(Thu, Jul 2)
9.3 Naive Bayes [PSet2 Coding]
No Lecture
(Fri, Jul 3)
No Class - July 4th Holiday
Week 3
Lecture 6
(Mon, Jul 6)
3.4 Zoo of Discrete RVs I
• PSet1 Due 11 PM PDT
Recitation 3
(Tues, Jul 7)
Indicator Random Variables, Expectation, and Variance
Lecture 7
(Wed, Jul 8)
3.5 Zoo of Discrete RVs II
3.6 Zoo of Discrete RVs III
Section 3
(Thu, Jul 9)
9.4 Bloom Filters [PSet3 Coding]
Lecture 8
(Fri, Jul 10)
4.1 Continuous Random Variables Basics
Week 4
Lecture 9
(Mon, Jul 13)
4.2 Zoo of Continuous RVs
Recitation 4
(Tues, Jul 14)
Zoo of Random Variables Practice
Lecture 10
(Wed, Jul 15)
4.3 The Normal Random Variable
4.4 Transforming Continuous RVs
• PSet2 Due 11 PM PDT
Section 4
(Thu, Jul 16)
9.5Distinct Elements [PSet3 Coding]
Lecture 11
(Fri, Jul 17)
5.1 Joint Discrete Distributions
• Project Proposal Due 11 PM PDT
Week 5
Lecture 12
(Mon, Jul 20)
5.2 Joint Continuous Distributions
Recitation 5
(Tues, Jul 21)
Continuous RVs and Joint Distributions
Lecture 13
(Wed, Jul 22)
5.3 Conditional Distributions
Section 5
(Thu, Jul 23)
Analyzing Probabilistic Data Structures (PDS) and Randomized Algorithms (RA)
Lecture 14
(Fri, Jul 24)
5.4 Covariance and Correlation
Week 6
Lecture 15
(Mon, Jul 27)
5.5 Convolution
Recitation 6
(Tues, Jul 28)
Conditional Expectation and Distributions, Covariance
Lecture 16
(Wed, Jul 29)
5.6 Moment Generating Functions
5.7 Limit Theorems
5.11 Proof of the CLT
5.6 video slides notes cc
5.7 video slides notes cc
5.11 video slides notes [no cc] (optional)
problems solutions
Section 6
(Thu, Jul 30)
Practice Problems
Lecture 17
(Fri, Jul 31)
9.6 MCMC [PSet4 Coding]
5.8 The Multinomial Distribution
5.9 Multivariate Normal Distribution
5.10 Order Statistics
9.6 slides notes [no cc] (in class)
5.8 video slides notes cc
5.9 video slides notes [no cc] (optional)
5.10 video slides notes [no cc] (optional)
problems solutions
Week 7
Lecture 18
(Mon, Aug 3)
7.1 Maximum Likelihood Estimation
7.2 Maximum Likelihood Examples
7.1 video slides notes cc
7.2 video slides notes [no cc] (in class)
problems solutions
• Project Milestone Due 11 PM PDT (optional)
Recitation 7
(Tues, Aug 4)
Convolution, MGFs, CLT, Multi-Distributions
Lecture 19
(Wed, Aug 5)
7.3 Method of Moments Estimation
7.4 Beta and Dirichlet Distributions
Section 7
(Thu, Aug 6)
Practice Problems
Lecture 20
(Fri, Aug 7)
7.5 Maximum a Posteriori Estimation
7.6 Properties of Estimators I
7.7 Properties of Estimators II
7.8 Properties of Estimators III
7.5 video slides notes cc (ec)(in class)
7.6 video slides notes cc (ec)(optional)
7.7 video slides notes cc (ec)(optional)
7.8 video slides notes cc (ec)(optional)
problems solutions
Week 8
Lecture 21
(Mon, Aug 10)
9.7 Bootstrapping [PSet5 Coding]
8.3 Introduction to Hypothesis Testing
9.7 slides notes [no cc] (in class)
8.3 video slides notes cc
problems solutions
Recitation 8
(Tues, Aug 11)
Hypothesis Tests, MLE, MoM, MAP
Lecture 22
(Wed, Aug 12)
8.1 Confidence Intervals
8.2 Credible Intervals
Section 8
(Thu, Aug 13)
Practice Problems
Lecture 23
(Fri, Aug 14)
9.8Multi-Armed Bandits [PSet5 Coding]
Week 9
Lecture 24
(Mon, Aug 17)
6.1 Markov & Chebyshev Inequalities
6.2 The Chernoff Bound
6.3 Even More Inequalities
6.1 video slides notes cc (ec) (in class)
6.2 video slides notes cc (ec) (in class)
6.3 video slides notes cc (ec) (optional)
• Project Due 11 PM PDT
Recitation 9
(Tues, Aug 18)
Office Hours + AMA
Lecture 25
(Wed, Aug 19)
How to Lie with Statistics
Section 9
(Thu, Aug 20)
TA's Choice
Lecture 26
(Fri, Aug 21)
Course Wrap Up!
PSet5 Due 11 PM PDT
(no late days allowed)

Note that content for future lectures is subject to change.

This course website heavily follows the example of the website of CSE373 2019 Spring.