**Semester** – Spring 2018

**Instructor** – Prasanna Chaporkar

**Pre-requisites** – A basic probability course – EE325

**Motivation** – Markov chains and queuing systems have wide and interesting applications in various domains. The problems discussed in class and tutorials are often those having practical relevance. The course content is really interesting, although sometimes may get a little math-heavy.

**Course content** – The course is mainly divided into two parts. In the first part, both continuous and discrete time Markov processes are covered, along with renewal reward theory. In the second part of the course, the theory of Markov chains is used in queuing systems. Various types of queuing models and scheduling policies were covered with relevant examples.

**Lectures and tutorials** – Attending lectures is really helpful, as there was not one particular resource from which sir taught the course. The lectures were moderately paced, although sometimes a tad bit slow. After the completion of each topic, sir uploaded a tutorial sheet, which was then discussed in a separate tutorial class (usually on weekends).

**Exams** – There were 6 quizzes and no midsem or endsem. Best 5 out of 6, each of 20 marks were considered for the total grade. All quizzes were open book – handwritten notes only. Each quiz had 8 marks worth of questions directly from the tutorial sheet given by sir on the topic. Each quiz was based on separate topics, and the syllabus for the consecutive quizzes did not add up. The quizzes were of moderate difficulty level. Attending classes and religiously solving the tutorial sheets would make the course proceed smoothly, and get a good grade.