Probability and Stochastic Processes

Lecture No.	Lecture Title	Course Material
0	Introduction
1	Set Theory
2	Functions and Countability
3	Prelude to Probability Spaces
4	Probability Spaces
5	A Primer on Combinatorial Probability
6	Conditional Probability and Independence
7	Random Variables
8	Discrete Random Variables
9	Continuous Random Variables
10	Functions of Random Variables
11	Expectation
12	Multiple Random Variables
13	Conditional Distribution
14	Functions of Random Vectors
15	Expectation Revisited
16	Conditional Expectation
17	Sequence of Random Variables
18	Concentration Bounds and Limit Theorems
19	Simulation of Random Variables
20	Stochastic Processes-I
21	Stochastic Processes-II
22	Discrete Time Markov Processes

P. Set No.	Problem Set Contents	Course Material
1	Sets, Functions, and Countability
2	Probability Spaces
3	Random Variables, Transformations, and Expectation
4	Joint and Conditional Distributions
5	Convergence and Concentration Bounds
6	Stochastic Processes