Surely a level-up from the previous courses. This course adds to and extends what has been learned in courses 1 & 2 to a greater sphere of real-world problems. Great job Prof. Adam and Martha!
Adam & Martha really make the walk through Sutton & Barto's book a real pleasure and easy to understand. The notebooks and the practice quizzes greatly help to consolidate the material.
von Chang, W C•
The course presentation is wonderful. I can't stop after I watch the first video.
von Rishi R•
It has amazing content with no compromise on concepts yet holds simplicity.
von Kaustubh S•
It was a wonderful course. To the point yet well-explained concepts.
von Max C•
I had a much better experience with the autograder than in course 2.
Everything is amazing in this course! Dont miss it!
von Pachi C•
Fantastic course and great content and teachers!!!
Excellent course! Never be replaced! Thank you!
von Raktim P•
Great Course! Highly recommended for beginners.
von İbrahim Y•
the course is the intro for high level RL
von MJ A•
perfect and thank you for this course
von Teresa Y B•
Very Useful and Highly Recommend !!!
von Stewart A•
Simply the best course on this topic.
Very good and self-oriented course!
von Wei J•
It is a very perfect RL course.
von Antonis S•
Really a well-prepared course!
von Ignacio O•
Really good, I learned a lot.
von FREDERIC N•
Great speakers and content!
von Majd W•
Very practical course.
Excellent class !!!
von Hugo T K•
von Murtaza K B•
von Ivan M•
von Oriol A L•
von Cheuk L Y•
von Ananthapadmanaban, J•
I am disappointed with policy gradients being introduced on last week of the 3rd course. The instructors need to understand that 12 weeks is too much for introduction before starting a good project to implement the concepts with a hope to better understand them (course 4). Policy gradients should have been introduced in week 3/4 of course 2 itself. The content before that should be made more efficient (4 weeks to understand until q-learning/sarsa and 2 weeks to understand function approximation should be enough). I realized after course 2 that Andrew Ng has 3/4 videos on RL in the recently released ML class from Stanford. I am yet to go through them, but I feel they may explain these faster with same amount of rigour. However, the stanford class assignments are not public, which makes this course still useful because of the assignments. However, thanks to the instructors for this course.