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Applied Stochastic Processes

By Prof. Swanand R. Khare, Prof. Amitalok J. Budkuley   |   IIT Kharagpur
Learners enrolled: 338   |  Exam registration: 3
ABOUT THE COURSE:

This course introduces fundamental concepts in stochastic processes which arises in the study of behavior of systems that appear commonly in electrical engineering, computer science, and applied mathematics, and that evolve randomly over time. The course topics include a quick review of foundational probability with a keen focus on conditional probability, discrete and continuous-time Markov chains, discrete and continuous time counting processes like Bernoulli and Poisson processes and their derivatives, renewal theory and the reward theorem, and Brownian motion. The course will emphasize both theory and applications of these concepts. Applications are drawn from a diverse set of areas such as queueing systems, communication networks, and event-driven modeling.

 Key topics: Probability distributions, conditional expectation, discrete and continuous-time Markov chains, discrete and continuous time counting processes including Bernoulli and Poisson processes, and their derivatives, renewal theory, Brownian motion, applications: stochastic modeling in queues and networks.

INTENDED AUDIENCE: Senior undergraduate and postgraduate students in Mathematics, ECE, EE, CSE

PREREQUISITES: Introductory course on Probability and Statistics
Summary
Course Status : Upcoming
Course Type : Elective
Language for course content : English
Duration : 12 weeks
Category :
  • Mathematics
Credit Points : 3
Level : Undergraduate
Start Date : 19 Jan 2026
End Date : 10 Apr 2026
Enrollment Ends : 26 Jan 2026
Exam Registration Ends : 13 Feb 2026
Exam Date : 19 Apr 2026 IST
NCrF Level   : 4.5 — 8.0

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.


Page Visits



Course layout

Week 1:  Preliminaries I: Introduction to probability, review of distributions: Bernoulli, Binomial, Poisson, Multinomial, Exponential, Gamma, Gaussian distribution

Week 2: Preliminaries II: Conditional probability, Conditional expectation and variance, Computations with conditioning, Central limit theorem, Software demonstration of simulating discrete and continuous random variables

Week 3: DTMC I: Discrete time stochastic processes, Discrete time Markov chains, transition probabilities, Chapman-Kolmogorov equations, classification of states, Software demonstration of the concepts

Week 4: DTMC II: Limiting probabilities, Connection to Perron Frobenius Theorem, Mean time spent in transient states, Branching processes, Time reversible Markov chains, Applications

Week 5: Discrete time counting processes: Bernoulli random processes, definitions and alternate synthesis approaches via interarrivals, properties, operating on Bernoulli processes like merging and splitting, Applications to simple discrete-time queues

Week 6: Continuous time counting processes: Poisson processes, Interarrival and waiting time distributions, merging and splitting operations, order statistics, conditional distribution on arrival times, marked and compound Poisson processes, Applications

Week 7: CTMC I: Birth and Death processes, Transition probability function.

Week 8: CTMC II : Kolmogorov’s backward and forward equations, Limiting probabilities, Applications

Week 9: Renewal : definitions, examples, Limit theorems, renewal reward, Applications to reliability

Week 10: Applications to Queuing theory: basic definitions of queues and Kendall notation, analysis of M/M/X/X queues

Week 11: Martingale and Brownian motion: definition, connections to other processes, Hitting times, Gambler’s ruin problem, Brownian motion with drift, Geometric Brownian motion, White noise, Gaussian processes, Stationary and weak stationary processes

Week 12: Applications: Option pricing, risk neutral pricing, Arbitrage theorem, Black Scholes option pricing formula

Books and references

1.Ross, Sheldon M. Introduction to Probability Models. Elsevier, 2023
2.Gallager, Robert G. Stochastic processes: theory for applications. Cambridge University Press, 2013.
3.Ross, Sheldon M. Stochastic processes. John Wiley & Sons, 1995.
4.Gangopadhyay S. and Chandra T.K. Introduction to Stochastic processes, Narosa Publishing House, 2018

Instructor bio

Prof. Swanand R. Khare

IIT Kharagpur
Prof. Swanand R. Khare obtained M.Sc. and Ph.D. degrees from IIT Bombay in 2005 and 2011 respectively. He was a post-doctoral researcher in the University of Alberta, Canada from 2011 to 2014 and then subsequently joined the Department of Mathematics at IIT Kharagpur. He currently works as an Associate Professor in the Department of Mathematics and jointly in the Centre of Excellence in AI at IIT Kharagpur. His research interests include inverse eigenvalue problems, computational linear algebra, estimation and computational issues in applied statistics. He has been actively participating in fundamental as well as applied research in these areas. He has supervised four PhD students and several masters’ students in their research work. He served as an Associate Editor for a journal named Control Engineering Practice for a period of three years from 2018 to 2021. He is a recipient of Excellent Young Teacher Award 2018 at IIT Kharagpur.


Prof. Amitalok J. Budkuley

Prof. Amitalok J. Budkuley received the B. Engg. degree in electronics and telecommunications engineering from Goa University, Goa, India, in 2007, and the M.Tech. and Ph.D. degrees in electrical engineering from the Indian Institute of Technology Bombay, Mumbai, India, in 2009 and 2017, respectively. From 2009 to 2010, he was with Cisco Systems Inc., Bengaluru, India. He was a Research Assistant and then a Post-Doctoral Researcher at the Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong, from 2016 to 2019. He joined the Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India, in 2019, where he is currently an Assistant Professor.
His research interests include wireless communications, information and coding theory, information-theoretic secrecy and cryptography, and stochastic signal processing for distributed communication and control.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.
The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).
Date and Time of Exams: April 19, 2026 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.
Registration url: Announcements will be made when the registration form is open for registrations.
The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.
Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Kharagpur .It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team
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