Textbook:
Dimitri P. Bertsekas and John N. Tsitsiklis Introduction to Probability, 2nd edition

Actual schedule (Fall 2018):

September 28
Sets and manipulating sets (Section 1.1)
October 1
Probability spaces (Section 1.2)
October 3
Conditional probability (Section 1.3)
October 5
Conditional probability: Total Probability and Bayes theorem (Section 1.4)
October 8
Total probability, Multiplication rule, starting Independence (from Sections 1.3-1.5)
October 10
Multiplication rule, Independence (book problem 25, Section 1.5)
October 12
Independence (Section 1.5)
October 15
Binomial coefficient and counting (Section 1.6)
October 17
Random variables, probability mass functions (Sections 2.1, 2.2)
October 19
MIDTERM 1
October 22
Probability mass function (Sections 2.2, 2.3)
October 24
Mean and Variance (Section 2.4)
October 26
Joint and marginal PMF of several random variables (Section 2.4)
October 29
Mean, variance, covariance, correlation coefficient of many RV (Sections 2.5, 4.2)
October 31
Conditional PMF (Section 2.6)
November 2
Independence (Section 2.7)
November 5
More on independence and conditional expectation (Sections 2.5-2.7)
November 7
Continuous random variables and PDF (Section 3.1)
November 9
Continuous random variables and PDF (Section 3.1, 3.3)
November 14
Review
November 16
MIDTERM 2
November 19
CDF of random variables (Section 3.2)
November 21
Normal random variables (Section 3.3)
November 26
Joint PDF (Section 3.4)
November 27
Conditioning in CTS case (Section 3.5)
November 29
Independence and CTS Bayes rule (Sections 3.5-3.6)
December 3
Law of Large numbers (Sections 5.1,5.2)
December 5
Central limit theorem (Section 5.3)
December 7
Review
December 10
FINAL EXAM