Lecture 1: Introductions, Counting
Lecture 2: Permutations and Combinations
Lecture 3: Axioms of Probability
Ross: Ch 2.1-2.5, 2.7
Lecture 4: Conditional Probability and Bayes
Ross: Ch 3.1-3.3
Section 1: Analytic Probability
Lecture 5: Independence
Ross: Ch 3.4-3.5
Lecture 6: Random Variables and Expectation
Ross: Ch 4.1-4.4
Lecture 7: Variance, Bernoulli, Binomial
Ross: Ch 4.5-4.6
Section 2: Random Variables and Expectation
Lecture 8: Poisson and Approximations
Ross: 4.7-4.10
Lecture 9: Continuous Random Variables
Ross: Ch 5.1-5.3, 5.5
Lecture 10: The Normal Distribution
PSet 2 In, PSet 3 Out
Ross: Ch 5.4
Lecture 11: Joint Distributions
Quiz 1 Out
Ross: Ch 6.1
Lecture 12: Independent Random Variables
Quiz 1 In
Ross: Ch 6.2-6.3
Lecture 13: Joint RV Statistics
Ross: Ch 6.4-6.5
Section 4: TBD
Ross: Ch 7.1-7.2
Lecture 14: Conditional Expectation
Ross: Ch 7.1-7.2
Lecture 15: General Inference
PSet 3 In, PSet 4 Out
No assigned reading.
Lecture 16: Continuous Joint Distributions
Ross: Ch 6.1
Lecture 17: Continuous Joint Distributions II
Ross: Ch 7.3-7.4
Lecture 18: Central Limit Theorem
Ross: Ch 8.3
Lecture 19: Sampling/Bootstrapping
PSet 4 In, PSet 5 Out
No assigned reading.
Section 6: TBD
No assigned reading.
Lecture 20: Parameters and MLE
Quiz 2 Out
Lecture 21: Beta
Quiz 2 In
Ross: Ch 5.6.1-5.6.4, 7.5-7.6
Lecture 22: Maximum a Posteriori
No assigned reading.
Lecture 23: Naive Bayes
No assigned reading.
Lecture 24: Gradient Ascent, Linear Regression
PSet 5 In, PSet 6 Out
No assigned reading.
Lecture 25: Logistic Regression
No assigned reading.
Lecture 26: Deep Learning I
No assigned reading.
Lecture 27: Deep Learning II
No assigned reading.
Memorial Day Holiday: No lecture
PSet 6 In
Lecture 28: Additional Topics
Quiz 3 Out
No assigned reading.
Lecture 29: The Future of Probability
Quiz 3 In
No assigned reading.
Note that all lectures and assignment deadlines are subject to change.
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