**Wed, May 12**: Quiz 2 is up and available right here. Problem Set 4 Solutions are also right here.

Week 1

Topic

Materials

Assignments

Optional Reading

Week 1

Wed, Mar 31

Lecture 2: Permutations and Combinations

Fri, Apr 2

Lecture 3: Axioms of Probability

Ross: Ch 2.1-2.5, 2.7

Week 2

Mon, Apr 5

Lecture 4: Conditional Probability and Bayes

Ross: Ch 3.1-3.3

Wed, Apr 7

Lecture 5: Independence

Ross: Ch 3.4-3.5

Fri, Apr 9

Lecture 6: Random Variables and Expectation

Ross: Ch 4.1-4.4

Week 3

Mon, Apr 12

Lecture 7: Variance, Bernoulli, Binomial

Ross: Ch 4.5-4.6

Wed, Apr 14

Lecture 8: Poisson and Approximations

Ross: 4.7-4.10

Fri, Apr 16

Lecture 9: Continuous Random Variables

Ross: Ch 5.1-5.3, 5.5

Week 4

Mon, Apr 19

Lecture 10: The Normal Distribution

Ross: Ch 5.4

Wed, Apr 21

Lecture 11: Joint Distributions

Ross: Ch 6.1

Fri, Apr 23

Lecture 12: Independent Random Variables

Quiz 1 In

Ross: Ch 6.2-6.3

Week 5

Mon, Apr 26

Lecture 13: Joint RV Statistics

Ross: Ch 6.4-6.5

Tue, Apr 27

Section 4: Normal Distributions and Joint RV Statistics

Ross: Ch 7.1-7.2

Wed, Apr 28

Lecture 14: Conditional Expectation

Ross: Ch 7.1-7.2

Fri, Apr 30

Lecture 15: General Inference

Week 6

Mon, May 3

Lecture 16: Continuous Joint Distributions

Ross: Ch 6.1

Wed, May 5

Lecture 17: Continuous Joint Distributions II

Ross: Ch 7.3-7.4

Fri, May 7

Lecture 18: Central Limit Theorem

Ross: Ch 8.3

Week 7

Mon, May 10

Lecture 19: Sampling/Bootstrapping

Wed, May 12

Lecture 20: Parameters and MLE

Fri, May 14

Lecture 21: Beta

Quiz 2 In

Ross: Ch 5.6.1-5.6.4, 7.5-7.6

Week 8

Mon, May 17

Lecture 22: Maximum a Posteriori

Wed, May 19

Lecture 23: Naive Bayes

Fri, May 21

Lecture 24: Ethics and AI

Week 9

Mon, May 24

Lecture 25: Practice with Naive Bayes

Wed, May 26

Lecture 26: Gradient Ascent, Linear Regression

Week 10

Mon, May 31

Tue, June 1

PSet 6 In

Wed, June 2

Lecture 28: Logistic Regression, Take II

Fri, Jun 4

Lecture 29: Deep Learning, Concluding Remarks

Quiz 3 In

Note that all lectures and assignment deadlines are subject to change.

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