PS 301 - Policy Related Supervised Learning

PS 301 - Policy Related Supervised Learning

Instructor:

Guide: Prof Jayendran V. , Instructor/Evaluator: Prof Shishir Jha

Motivation to take this course:

Gain exposure to parameters evaluated when formulating policy and real world concerns in implementation

Sections:

Open for all

Semester:

Autumn ‘19

Course Difficulty:

Easy

Time commitment required:

Expectation is 3 hours a week as it is a 3 credit course. In reality it depends on the Project/Guide and the student

Attendance Policy:

N/A. Weekly meetings with the Prof

Grading Policy and Statistics:

NA

Prerequisites:

Ability to read copious amount of data/articles and synthesize findings

Evaluation Scheme:

Grades are based on final report preparation and presentation to the evaluator and some weightage given to inputs from the project guide. You will be evaluated on the amount and quality of effort put into the project.

Course Contents (in brief):

Completely project dependent. I worked on a Policy review of Electric vehicles in India.

How strongly would you recommend someone for taking this course?

If you are looking forward to self learning and exposure to policy making I would recommend this course.

Feedback on Exams:

The exams require writing long answers but do not need rote learning.

Review by: Rishabh Dsouza