Course abstract
Reinforcement learning is a paradigm that aims to model the trial-and-error learning process that is needed in many problem situations where explicit instructive signals are not available. It has roots in operations research, behavioral psychology and AI. The goal of the course is to introduce the basic mathematical foundations of reinforcement learning, as well as highlight some of the recent directions of research.
Course Instructor
Prof. Balaraman Ravindran
Prof. Balaraman Ravindran is currently a Professor in Computer Science at IIT Madras. He has nearly two decades of research experience in machine learning and specifically reinforcement learning. Currently his research interests are centered on learning from and through interactions and span the areas of data mining, social network analysis, and reinforcement learning.More info
Teaching Assistant(s)
Course Duration : Jul-Oct 2019
View Course
Syllabus
Enrollment : 15-May-2019 to 05-Aug-2019
Exam registration : 01-Jun-2019 to 30-Sep-2019
Exam Date : 16-Nov-2019, 16-Nov-2019
Enrolled
2204
Registered
95
Certificate Eligible
57
Certified Category Count
Gold
1
Silver
3
Elite
22
Successfully completed
31
Participation
12
Success
.jpg)
Category : Successfully Completed
Elite
.jpg)
Category : Elite
Silver
.jpg)
Category : Silver
Gold
.jpg)
Category : Gold
Legend
AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed
Final Score Calculation Logic
- Assignment Score = Average of best 8 out of 12 assignments.
- FINAL SCORE (Score on Certificate) = 75% of Exam Score + 25% of Assignment Score.
Reinforcement Learning - Toppers list
Enrollment Statistics
Total Enrollment: 2204
Registration Statistics
Total Registration : 95
Assignment Statistics
Assignment
Exam score
Final score
Exam score
Final score