Spring 2020-21
Prof. Debasish Chatterjee
Author: Ayush Sarraf
Pre-requisite courses: No hard prerequisites, but basic knowledge of elementary probability theory is a plus
Pre-requisite skills: No skills as such is required, but little knowledge of python/MATLAB can be used at the end to try some basic Monte-Carlo simulations taught in class.
Course Content: Kindly check ASC for the updated course contents
Motivation to take up the course: To learn more about different probabilistic tools used in modelling processes and also the course could be tagged as a DS minor elective
Information about Projects/Assignments: The assignments were very mathematical and required quite a bit of effort and also very lengthy.
Assignments Difficulty: 5/5
Quizzes/Midsem/Endsem papers Difficulty: 4/5
Evaluation Structure: 2 quizzes - 15% each endsem - 25% 2 assignments - 15% each viva - 15%
Lecture Style and Delivery: The lectures were very mathematical and the prof did not get into the gory details of everything. Proofs were left with hints and expected the students to figure out.
Attendance Policy: None
General funda: Try to attend as many lectures as possible and do attempt the questions highlighted by the prof in class. Also, do not skip mathematical proofs!
Who can take this course?: Anyone who wants to learn about probability theory and can handle decent amount of mathematics.