Course Outline: 

Sample spaces, events, axioms of probability (Ch. 2)

Some elementary combinatorics. Combinations and permutations (Ch. 1)

Conditional probabilities, independence and Bayes Formula (Ch. 3)

Discrete random variables (Ch. 4) and Continuous random variables (Ch. 5)

Joint distributions, marginal distributions and conditional distributions (Ch. 6)

Expectation: sums, covariance, moment generating functions (Ch. 7)

Limit Theorems: weak law of large numbers, central limit theorem (Ch. 8)
You can find a course syllabus here.
