Instructor

Prof. Nikhil Karamchandani

Semester

Spring 2023

Course Difficulty

Overall, the content is intellectually stimulating and most concepts are easy to understand in class. However, there are some topics that might need more work done on your own but these are quite elegant and important from the point of view of applications in ML.

Time commitment needed

Apart from classes and tutorials, time had to be dedicated to solving the homeworks, each of which didn�t take more than 3 hours. Apart from that, not much time commitment is required assuming you don�t miss any class or tutorial discussions.

Grading Statistics

AA - 1 AB - 2 BB - 5 FR - 9 Out of a total 36 students. Though these numbers might seem disheartening to some, it should not be too difficult to get >= 8 if you attend class and tutorials regularly.

Attendance Policy

Attendance wasn�t compulsory but 5% of the final course total came from class participation.

Teaching Style

Content was mostly taught in the traditional way - using board and chalk and was quite effective. We had to take notes as no other material was shared and the class notes were exhaustive enough. So you cannot afford to miss class. Apart from the lectures, we also had tutorial sessions held almost bi-weekly. We had the most amazing TAs and the discussions we had during the tutorial sessions helped develop a stronger sense of appreciation of the topics discussed in lecture hours. I would highly encourage everyone to diligently attempt the tutorial questions and be attentive during the discussions.

Feedback on Exams (Written Evaluation)

The quizzes and midsem were easy if you were well-versed with the homeworks and tutorials. The endsem was slightly tougher and required greater understanding and problem solving ability. All exams were open handwritten notes.

Future Tracks

Taking it in 2nd year would be most ideal so you can take advance probability and theoretical ML courses in later semesters. If you enjoyed EE325, there are many electives in EE, CS, SI and IEOR that you might consider taking. Some of those are : EE621, EE734, IE708, CS747, IE618, SI404

Course Importance

I loved Probability ever since it was formally introduced to me back in school and even during JEE. Also, the course fell in the DS-minor basket. I�d highly recommend this course to anyone who liked the probability taught during JEE or someone who is getting into theoretical ML. This is also a good starting course for anyone who wants to strengthen their quant.

Additional Details

Course Highlights Some Elegant Probability Bounds and Applications. Best set of TAs.

Peers It’s a core course for the EE folks who usually take it in the odd semester. But it also runs in the even semester with a relatively small class size. This course is included in both the DS as well as EE minor baskets, so now you know who your peers are going to be :)

References Books Probability and Random Processes, Grimett and Stirzaker https://www.vfu.bg/en/e-Learning/Math�Bertsekas Tsitsiklis Introduction to probability.pdf Probability, Random Variables and Stochastic Processes, Papoulis and Pillai A first course in probability, S. Ross One Thousand Exercises in Probability by Grimmett and Stirzaker.

Written By

Utkarsh Chavan