Adam Blank

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Welcome to CSE 312! We have put the most important links at the top, categorized by what they're for. Please check them out!

It is very important to us that you succeed in CSE 312. We provide many extra resources to help you. Adam and the TAs
hold many office hours, we have a message board called
, and we provide you with many practice handouts.

It is also very important to us that you maintain your mental wellness throughout the course. A few points are not worth losing sleep over.
Everyone on the course staff is available to chat, and you can always attend office hours for a non-academic conversation if necessary.
You can use the following resources if you find you need help beyond the course staff:

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Day

Topic

Homework

Combinatorics: Combinatorial Toolbox & Combinatorial Primitives

Combinatorics: Binomial Coefficients, Multinomial Coefficients, Counting in Two Ways

Section

Combinatorics: Counting in Two Ways & The Binomial Theorem

Combinatorics: Pigeonhole Principle & Inclusion-Exclusion

Combinatorics: Combinatorial Recurrences

Section

Discrete Probability: Axioms & Equally-Likely Outcomes

Discrete Probability: Conditional Probability & Law of Total Probability

Application: Fischer-Yates Shuffle & Reservoir Sampling

Section

Discrete Probability: Bayes' Theorem

Discrete Probability: Independence

Discrete Probability: Random Variables, Expectation, and Geometrics

Section

Discrete Probability: Linearity of Expectation

Application: Naive Bayes Classifier

Discrete Probability: Variance

Section

Discrete Probability: Independent Random Variables, Uniform, Bernoulli, Binomial

Application: Error-Correcting Codes and Poisson Distribution

Application: Quicksort, Matrix Multiplication

Section

Application: Primality Testing

Continuous Probability: Introduction, RVs, Uniform Distribution

Section

Continuous Probability: Exponential Distribution

Continuous Probability: Normal Distribution and The Central Limit Theorem

Continuous Probability: More CLT and Law of Large Numbers

Section

Probability Bounds: Markov, Cheyshev, Chernoff

Application: Hashtables and Bloom Filters

Application: Markov Chains and Pagerank

Section

Machine Learning: Maximum Likelihood Estimators

Machine Learning: Topic TBD

Machine Learning: Topic TBD

Section

Victory Lap