Back to Fundamentals of Reinforcement Learning

4.8

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1,455 ratings

•

368 reviews

Reinforcement Learning is a subfield of Machine Learning, but is also a general purpose formalism for automated decision-making and AI. This course introduces you to statistical learning techniques where an agent explicitly takes actions and interacts with the world. Understanding the importance and challenges of learning agents that make decisions is of vital importance today, with more and more companies interested in interactive agents and intelligent decision-making.
This course introduces you to the fundamentals of Reinforcement Learning. When you finish this course, you will:
- Formalize problems as Markov Decision Processes
- Understand basic exploration methods and the exploration/exploitation tradeoff
- Understand value functions, as a general-purpose tool for optimal decision-making
- Know how to implement dynamic programming as an efficient solution approach to an industrial control problem
This course teaches you the key concepts of Reinforcement Learning, underlying classic and modern algorithms in RL. After completing this course, you will be able to start using RL for real problems, where you have or can specify the MDP.
This is the first course of the Reinforcement Learning Specialization....

AT

Jul 07, 2020

An excellent introduction to Reinforcement Learning, accompanied by a well-organized & informative handbook. I definitely recommend this course to have a strong foundation in Reinforcement Learning.

NH

Apr 08, 2020

This course is one of the best I've learned so far in coursera. The explanations are clear and concise enough. It took a while for me to understand Bellman equation but when I did, it felt amazing!

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By David R

•Dec 03, 2019

I really liked this course. I think it was challenging and high quality. I don't understand complaints about it following the book - I found the videos, quizzes and exercises insightful and thought provoking. And besides courses are meant to follow some material and not re-invent the wheel. Am really excited for the rest of the specialization.

By Nicolas

•Nov 20, 2019

The course was great. Very clearly explained, with meaningful examples and backup material, such as the recommended book.

My only comment will be on the case study given on the final programming assignment. The parking scenario was not very intuitive or clear for me. It took me quite a bit to understand what it was we were trying to optimize.

By Jesse W

•May 10, 2020

Excellent course. Covers all the basics at just the right challenge level, assuming you've had some Python programming experience and know a thing or two about probabilities and expectation values. They provide a PDF for a course textbook which is extremely well-written, and the videos are high-quality and complement the readings well.

By Mouafek A

•Apr 13, 2020

After studying Classical Machine Learning and Deep Learning, and applying them in real-life cases with some startups and companies, some aspects of day to day problems did not seem to be fit while trying to use the previous methods, thus I dived into Reinforcement Learning looking for answers, and so far it's been very promising!

By LUIS M G M

•Oct 25, 2019

I started to read Sutton & Barto book this summer, and although I find it fantastic, some concepts were not 100% clear to me. This course has changed it dramatically. Now every concept is clear to me. This book is like reading a book with the support of very good explanations.

Let's go for the 2nd course in the specialitation!!!

By Zhuang J

•Mar 24, 2020

You really need to understand fundamentals before kick start for any real world reinforcement learning problem. That's why this course is very essential. Plus it also provides programming tasks and multi-choice question sheet to deepen your understanding about theories. Great! Looking forward to move on for next series!

By Shashank S

•Apr 13, 2020

This course was a great first introduction to reinforcement learning! The course instructors make the material very accessible and the course follows the textbook very closely. I'd definitely recommend it to anyone trying to understand reinforcement learning and I personally plan to complete the entire specialization.

By Stelios S

•May 11, 2020

This is the BEST course I've taken from Coursera, period. The level of explanation, the usage of mathematically precise terminology, the walking through of the algorithms, the summaries were all top-notch. This course will be my reference when I forget something in the future. I can't thank the creators enough.

By Ali N

•Apr 01, 2020

It was a very good course, I had read Sutton's book first. But I must say that after completing this course, I learned the concepts of the book well. Although the exercises were a bit tough, they covered the topics well and increased learning at a faster rate.

For anyone interested, I recommend this course.

By Alejandro A Z

•Jul 20, 2020

It was really cool! Although I think there should be a forum where students could ask and answer questions. I got stuck for a silly mistake before delivering the last python notebook and could have used some help.

Still, I learnt an incredible amount of concepts that I didn't imagine were so important!

By Иванов К С

•Aug 29, 2019

It's difficult to estimate this course because it's based on the book. I mean, 90% of materials i've seen on videos were on the book. That's very unusual, but effective. However, i've learned necessary information and python tasks were useful and interesting. I'll take the next course and will see.

By Nicolas T

•Apr 26, 2020

Great course! The idea of suggesting reading before the videos gives a huge boost to the depth of the class. This, with the "not-too-straightforward-quizzes", and the assignments, makes it a real deep class, from which I'll probably learn and retain more than most online courses. Good job!

By Anton P

•Dec 15, 2019

It is a very well laid out and taught course. The instructors make the material accessible with a bit of a mathematics background, or a willingness to learn. I will be taking every machine learning course I can from AMII and the UofA if the rest of the courses are of the same quality.

By Sandesh J

•Jun 01, 2020

One of the best available courses on Reinforcement Learning. The instructors have explained all the underlying topics elegantly. Good blend of theory and numerical in assignments and programming problems. Moreover, the assignments have covered different perspectives on these topics.

By Giulio C

•Jun 25, 2020

Amazing course!

The book, on which this course is based, is a bible for reinforcement learning. Anyway, it could be hard to understand. The lectures of the course eliminate all doubts and consolidate all the concepts, ensuring a complete comprehension on the subject.

Thank you!

By Bae,Bongsung

•Apr 20, 2020

Great starting point for learning Reinforcement Learning. Anyone who is interested in the state-of-the-art RL techniques should take this course first, or they will have hard time getting through the more applied and sophisticated concepts found in the tech blogs or papers.

By Majd W

•Oct 24, 2019

The thing that makes this course outstand among other Coursera courses is that it is based on a book. That gives you more information if you need it.

One problem that I guess will be solved in the future is that there is a bug in the Programming Assignment submission code.

By Juan C E

•Feb 09, 2020

Excellent course. Excellent teachers. I love the introduction sections, in which you're presented what you'll learn in each video, and the summary section. The animated slides are also very professional. Very thorough coverage of the RL book. Congratulations!!!

By Rohit P

•Jul 25, 2020

Some supplementary video recommendations and a little more interactive help with the Python assignments would make it more fun. Had to struggle with the programming assignments a little bit. More hands on assignments will help drive home the concepts better.

By Yover M C C

•Mar 02, 2020

Excelente curso, aprendí los conceptos de aprendizaje por refuerzo con gran base teórica, el material del curso es muy bueno y la calidad de las lecturas es de excelente nivel. Muy recomendado, ahora a aprender más y a desarrollar sistemas inteligentes :).

By Le Q A

•Aug 02, 2020

Excellent introduction. The reading materials are good, the videos make the ideas even clearer and the exercises help us get a taste of how the theory could be applied. I would recommend this course to anyone wanting to start on Reinforcement Learning.

By Evgeny S

•Apr 18, 2020

I enjoyed the course. I would have preferred a bit more in-depth look at the algorithms and technical details, but, on the other hand, it was also interesting to go and figure out these contraction mapping arguments on your own. Overall, very good.

By Leelamohan

•Feb 16, 2020

I had learned a clear understanding of terminology and the formulas of value function, action-value function, optimal value function, Bellman's equation, policy evaluation and iteration. It's a must go through course for Reinforcement Learning

By Manuel

•Jul 22, 2020

The most professionally presented course I have done on Coursera! Instructors explain well, the provided literature is on point and the assignments had a good mix of being doable and challenging. Probably the best course I have taken so far.

By Damian K

•Sep 01, 2019

Slow means smooth. Smooth means fast. This course introduces you efficiently into the world of RL. And this is what you want. Everything is perfectly to the point. All exercise are here to boost your understanding. Highly recommended.

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