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Learner Reviews & Feedback for Sample-based Learning Methods by University of Alberta

945 ratings
192 reviews

About the Course

In this course, you will learn about several algorithms that can learn near optimal policies based on trial and error interaction with the environment---learning from the agent’s own experience. Learning from actual experience is striking because it requires no prior knowledge of the environment’s dynamics, yet can still attain optimal behavior. We will cover intuitively simple but powerful Monte Carlo methods, and temporal difference learning methods including Q-learning. We will wrap up this course investigating how we can get the best of both worlds: algorithms that can combine model-based planning (similar to dynamic programming) and temporal difference updates to radically accelerate learning. By the end of this course you will be able to: - Understand Temporal-Difference learning and Monte Carlo as two strategies for estimating value functions from sampled experience - Understand the importance of exploration, when using sampled experience rather than dynamic programming sweeps within a model - Understand the connections between Monte Carlo and Dynamic Programming and TD. - Implement and apply the TD algorithm, for estimating value functions - Implement and apply Expected Sarsa and Q-learning (two TD methods for control) - Understand the difference between on-policy and off-policy control - Understand planning with simulated experience (as opposed to classic planning strategies) - Implement a model-based approach to RL, called Dyna, which uses simulated experience - Conduct an empirical study to see the improvements in sample efficiency when using Dyna...

Top reviews

Aug 11, 2020

Great course, giving it 5 stars though it deserves both because the assignments have some serious issues that shouldn't actually be a matter. All the other parts are amazing though. Good job

Jan 9, 2020

Really great resource to follow along the RL Book. IMP Suggestion: Do not skip the reading assignments, they are really helpful and following the videos and assignments becomes easy.

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76 - 100 of 189 Reviews for Sample-based Learning Methods

By Chintan K

Jul 22, 2020

the course videos were short and precise , which makes the learning content fun and informative

By Wang G

Oct 19, 2019

Very Nice Explanation and Assignment! Look forward the next 2 courses in this specialization!

By Sodagreenmario

Sep 18, 2019

Great course, but there are still some little bugs that can be fixed in notebook assignments.

By Chris D

Apr 18, 2020

Very good. Minor issues with inconsistency between parameter naming in different exercises.

By Sirusala N S

Jul 30, 2020

The concepts were explained very clearly. The assignments were helpful in understanding.

By koji t

Oct 6, 2019

I made a lot of mistakes, but I learned a lot because of that.

It ’s a wonderful course.

By Sérgio V C

Mar 15, 2021

A good course to learn the basics of Monte Carlo methods for RL, as well as TD-methods!

By Louis S

Jun 5, 2020

Excellent content. The fact that it follows Sutton and Barto's TextBook is a must.

By Pruthvi J

Feb 7, 2021

Excellent course, gives a decent theoretical and practical introduction to RL.

By Ding L

Apr 24, 2020

By taking the class, I learned much more than only reading the textbook.

By Ofir E

Mar 22, 2020

Amazing course, truly academy-grade. And RL is such a fascinating topic!

By Fabrice L

Nov 14, 2020

Things start to get interesting in this course of the specialization.

By Sourav G

Mar 10, 2020

It was a very good course. All the concepts were explained very well.

By Varun K R K

May 15, 2021

The best course available on entire world for reinforcement learning

By Animesh

May 28, 2020

this course is very well designed and executed. wow! i loved it :D

By Li W

Mar 30, 2020

Very good introductions and practices to the classic RL algorithms


Jul 8, 2020

Great learning Experience and really helpful lecturers and staff.

By Rudi C

Jul 21, 2020

Wonderful course, highly instructive, and follows the textbook!

By Rajesh

Jul 2, 2020

Please make assignments more explanatory and allow flexiblity

By alper d

Jan 17, 2021

Good course material and simplified explanations. Thank you.

By David P

Nov 3, 2019

Really a wonderful course! Very professional and high level.

By Teresa Y B

Apr 10, 2020

Very well structured course, Thanks for so nice preparing!!

By Shi Y

Nov 10, 2019


By Alex E

Nov 19, 2019

A fun an interesting course. Keep up the great work!

By Jicheng F

Jul 11, 2020

Martha and Adam are great instructors, great job!