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 : Jan-Apr 2020
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Enrollment : 18-Nov-2019 to 03-Feb-2020
Exam registration : 16-Dec-2019 to 20-Mar-2020
Exam Date : 25-Apr-2020
Enrolled
3464
Registered
110
Certificate Eligible
54
Certified Category Count
Gold
1
Silver
8
Elite
16
Successfully completed
29
Participation
31
Success
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Category : Successfully Completed
Elite
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Category : Elite
Silver
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Category : Silver
Gold
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Category : Gold
Legend
AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40BASED 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 Note: We have taken best assignment score from Both Jan and July course
Reinforcement Learning - Toppers list
Enrollment Statistics
Total Enrollment: 3464
Registration Statistics
Total Registration : 229
Assignment Statistics
Assignment
Exam score
Final score
Exam score
Final score