NOC:Advanced Topics in Probability and Random Processes

Lecture 1 - Probability Basics

Lecture 2 - Random Variable - I

Lecture 3 - Random Variable - II

Lecture 4 - Random Vectors and Random Processes

Lecture 5 - Infinite Sequence of Events - I

Lecture 6 - Infinite Sequence of Events - II

Lecture 7 - Convergence of Sequence of Random Variables

Lecture 8 - Weak Convergence - I

Lecture 9 - Weak Convergence - II

Lecture 10 - Laws of Large Numbers

Lecture 11 - Central Limit Theorem

Lecture 12 - Large Deviation Theory

Lecture 13 - Crammer's Theorem for Large Deviation

Lecture 14 - Introduction to Markov Processes

Lecture 15 - Discrete Time Markov Chain - 1

Lecture 16 - Discrete Time Markov Chain - 2

Lecture 17 - Discrete Time Markov Chain - 3

Lecture 18 - Discrete Time Markov Chain - 4

Lecture 19 - Discrete Time Markov Chain - 5

Lecture 20 - Continuous Time Markov Chain - 1

Lecture 21 - Continuous Time Markov Chain - 2

Lecture 22 - Continuous Time Markov Chain - 3

Lecture 23 - Martingale Process - 1

Lecture 24 - Martingale Process - 2