Basic Information
- Course Code: EE 621
- Course Name: Markov Chains and Queuing Systems
- Course Offered In: 2023-2024
- Semester Season: Spring
- Instructors: Prof. P. Chaporkar
- Prerequisites: EE325 or any other basic probability course.
- Difficulty (1 being easy and 5 being tough): 4
Course Content
Discrete and Continuous Time Markov Chains in the first half and Renewal Processes and a bit about Queueing Systems in the second half.
Feedback on Lectures
The lectures tend to be more theory-oriented, with question solving done during weekly tutorials. The first half of the course is pretty intuitive and covers a few classic questions like the “Gambler’s Ruin”. The second half becomes more hardcore theory with a lot more emphasis on the mathematical side including derivations. The lectures give a basic understanding of the concepts, but it would be recommended to practice more questions and gain an intuition to solve the different kinds of problems for the exams. The lectures were slow initially but pretty soon picked up the pace. No attendance policy. The tutorials were held on alternate weekends and had questions about the topics covered in the preceding weeks.
Feedback on Evaluations
A total of 7 quizzes were conducted, the marking scheme being a best 5 out of the 7 with a weightage of 20% each. The midsem and endsem were equivalent to 1 and 2 quizzes respectively. All quizzes were open book with hand written notes only allowed. The portions of the quizzes were cumulative but with more emphasis on the more recent topics. The quizzes contained questions almost identical to the tutorial problems or with a small twist and could be solved with adequate practice and sincerely attending the lectures.
Study Material and Resources
Stochastic Processes by Sheldon Ross
Follow-up Courses
EE 736 : Introduction to Stochastic Optimization
Final Takeaway
If you’re interested in probability and want to continue from where EE 325 left off, this is a great course.