CSE 312: Foundations of Computing II, Autumn 2021

Announcements and Updates

Schedule

Week 1
Topic
Materials
Week 1
Lecture 1
(Wed, Sept 29)
Introduction
So you think you can count?

Section 1
(Thurs, Sept 30)
Counting Problems
Lecture 2
(Fri, Oct 1)
More Counting
Week 2
Lecture 3
(Mon, Oct 4)
No More Counting Please!
Lecture 4
(Wed, Oct 6)
Discrete Probability

Section 2
(Thurs, Oct 7)
Probability problems
Probability via coding
Lecture 5
(Fri, Oct 8)
Conditional Probability
Bayes Theorem
Week 3
Lecture 6
(Mon, Oct 11)
Independence
Chain Rule
Lecture 7
(Wed, Oct 13)
More conditional probability
Independence

Section 3
(Thurs, Oct 14)
Naive Bayes Classifier
Lecture 8
(Fri, Oct 15)
Intro Random Variables
Expectation
Week 4
Lecture 9
(Mon, Oct 18)
Linearity of Expectation
Lecture 10
(Wed, Oct 20)
Application: Bloom Filters
LOTUS

Section 4
(Thurs, Oct 21)
Random variables
Lecture 11
(Fri, Oct 22)
Variance
Independence of R.V.s
Week 5
Lecture 12
(Mon, Oct 25)
Zoo of Discrete RVs
Lecture 13
(Wed, Oct 27)
Poisson Random Variables

Section 5
(Thu, Oct 28)
The zoo
Lecture 14
(Fri, Oct 29)
Continuous R.V.s
Week 6
Lecture 15
(Mon, Nov 1)
Exponential and Intro to Normal R.V.s
Lecture 16
(Wed, Nov 3)
Normal RVs
Central Limit Theorem
Section 6
(Thurs, Nov 4)
Continuous random variables
Lecture 17
(Fri, Nov 5)
Application: Polling
Confidence Intervals
Week 7
Lecture 18
(Mon, Nov 8)
More CLT
Continuity Correction
Lecture 19
(Wed, Nov 10)
Application: Distinct Elements
(Thurs, Nov 11)
  • No Section: Veteran's Day
Lecture 20
(Fri, Nov 12)
Joint Distributions
Week 8
Lecture 21
(Mon, Nov 15)
Continuous Joint Distns
Conditional Expectation
Law of Total Expectation
(Wed, Nov 17)
Class cancelled

Section 7
(Thurs, Nov 18)
Joint distns; LTE
Lecture 22
(Fri, Nov 19)
Maximum Likelihood Estimation
Week 9
Lecture 23
(Mon, Nov 22)
Maximum Likelihood Estimation
Lecture 24
(Wed, Nov 24)
Markov Chains

Section
(Thurs, Nov 25)
  • No Section: Thanksgiving Holiday
No Lecture
(Fri, Nov 26)
  • No Lecture: Thanksgiving Holiday
Week 10
Lecture 25
(Mon, Nov 29)
Markov chains cont.
Lecture 26
(Wed, Dec 1)
Pagerank and tail bounds.
Section 8
(Thurs, Dec 2)
Lecture 27
(Fri, Dec 3)
Multivariate Gaussians and mixture models
Week 11
Lecture 28
(Mon, Dec 6)
Application: Auctions
Lecture 29
(Wed, Dec 8)
How People Lie with Statistics
Section 9
(Thurs, Dec 9)
Lecture 30
(Fri, Dec 10)
Victory lap!
Finals Week
(Mon, Dec 13)

Note that content for future lectures is subject to change.

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