EE 734 – ADVANCED PROBABILITY AND RANDOM PROCESSES FOR ENGINEERS

Course offered in:

Autumn 2020

Instructors:

Prof. Vivek Borkar

Course Content:

Probability spaces, random variables, expectation, stochastic convergence, independence, conditioning, Martingales, and Markov chains. Please note that even the initial topics like expectation and conditioning are not trivial topics.

Prerequisites:

Nothing was mentioned but it would be hard without EE223 or EE325.

Feedback on Lectures:

The class can get monotonous and it was difficult to concentrate on what was going on in the class. The professor tends to make statements about related topics like continuous Markov chains etc which, even though are very interesting to those who have some background on it, can make things very difficult to follow. The professor can end up teaching a lot of concepts in each lecture – so it can be difficult to pay attention to everything.

However, these digressions are not present in the slides and one can asynchronously learn the concepts from the slides and from online resources. The lectures were more insightful when we listened to the recordings later after going through the slides.

Feedback on Tutorials, Assignments and Exams:

Exams were very easy compared to the syllabus. Practice problems were very useful for the exams.

Difficulty:

9 out of 10, but exams were very easy so getting a good grade isn’t difficult

Grading Statistics:

Study Material and References:

Professor provides slides

Comments:

Need to pay attention to every line in the proofs discussed in class

Advanced courses that can be taken after this:

EE736: Introduction to Stochastic Optimisation

Takeaways from the course:

Martingale theory is central to analysis of many reinforcement learning/optimal control algorithms.

Sponsored Content