Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.


Advanced Topics in Probability and Random Processes

NPTEL and Indian Institute of Technology Guwahati via YouTube


Course Intro: The course will cover mainly two broad areas: (1) the concepts of the convergence a sequence of random variables leading to the explanation of important concepts like the laws of large numbers, central limit theorem; and (2) Markov chains that include the analysis of discrete and continuous time Markov Chains and their applications.

Pre Requisites: Basic Course in Probability


Advanced Topics in Probability and Random Processes.
Lec 1: Probability Basics.
Lec 2: Random Variable-I.
Lec 3: Random Variable-II.
Lec 4: Random Vectors and Random Processes.
Lec 5: Infinite Sequence of Events-l.
Lec 6: Infinite Sequence of Events-ll.
Lec 7: Convergence of Sequence of Random Variables.
Lec 8: Weak Convergence-I.
Lec 9: Weak Convergence-II.
Lec 10: Laws of Large Numbers.
Lec 11: Central Limit Theorem.
Lec 12: Large Deviation Theory.
Lec 13: Crammer's Theorem for Large Deviation.
Lec 14: Introduction to Markov Processes.
Lec 15: Discrete Time Markov Chain.
Lec 16: Discrete Time Markov Chain-2.
Lec 17: Discrete Time Markov Chain-3.
Lec 18: Discrete Time Markov Chain-4.
Lec 19: Discrete Time Markov Chain-5.
Lec 20: Continuous Time Markov Chain - 1.
Lec 21: Continuous Time Markov Chain - 2.
Lec 22: Continuous Time Markov Chain - 3.
Lec 23: Martingle Process-1.
Lec 24: Martingle Process-2.

Taught by

NPTEL IIT Guwahati

Related Courses

Related articles


Start your review of Advanced Topics in Probability and Random Processes

Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free