Jan 10, 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.
Oct 03, 2019
Great course! The notebooks are a perfect level of difficulty for someone learning RL for the first time. Thanks Martha and Adam for all your work on this!! Great content!!
por Kaiwen Y•
Oct 02, 2019
I spend 1 hour learning the material and coding the assignment while 8 hours trying to debug it so that the grader will not complain. The grader sometimes insists on a particular order of the coding which does not really matter in the real world. Also, grader inconsistently gives 0 marks to a particular part of the problem while give a full mark on other part using the same function. (Like numpy.max) However, the forum is quite helpful and the staff is generally responsive.
Sep 23, 2019
Rating 4.3 stars – so far (first two classes combined)
Programming assignments: 4.5stars
Book (Sutton and Barto): 4.5stars
In the spectrum from the theoretical to practical where you have, very roughly,...
(1) “Why”: Why you are doing what you are doing
(2) “What”: What you are doing
(3) “How”: How to implement it (eg programming)…
...this is a “what-how” class.
To cover the “why-what” I strongly recommend augmenting this class with David Silver’s lectures (on Youtube) and notes from a class he gave at UCL. This covers more of the theory/math behind RL but covers less on the coding. Combined together with this class it probably comprises the best RL education you can get *anywhere*, creating a 5-star combo.
por Ivan S F•
Sep 29, 2019
Great course. Clear, concise, practical. Right amount of programming. Right amount of tests of conceptual knowledge. Almost perfect course.
por Manuel B•
Nov 28, 2019
Great course! Really powerful but simply ideas to solve sequential optimization problems based on learning how the environment works.
por Manuel V d S•
Oct 04, 2019
Course was amazing until I reached the final assignment. What a terrible way to grade the notebook part. Also, nobody around in the forums to help... I would still recommend this to anyone interested, unless you have no intention of doing the weekly readings.
por Maxim V•
Jan 12, 2020
Good content, but a lot of annoying issues with grader.
Jan 25, 2020
This course is ok if you're reading the Sutton & Barto RL book and would like to have some quizzes to follow along. The programming assignments are not really "programming" because you're constrained to type a handful of lines in a few places into a solution that is largely has been prepared for you. With "hints" like "# given the state, select the action using self.choose_action_egreedy(),
# and save current state and action (~2 lines)
### self.past_state = ?
### self.past_action = ?"
it is impossible to get them wrong. These exercises are ok as labs (comparing various algorithms, etc), but the programming part can be done by rote. Coursera has classes with more intense and creative programming assignments and the learning there seems to be much deeper.
por Andrew G•
Dec 24, 2019
The course needs more support and / or error message output for the programming assignments. Code that seems correct can easily fail the autograder, and the only method of recourse is posting in the forums, which may or may not be received by a moderator.
por Bernard C•
Mar 22, 2020
Course was good but assignment graders were terrible.
por Juan C E•
Mar 07, 2020
Many mistakes with grading and 100% penalty applied for tasks not completed on time, when the rules say that you can submit your assignments and do your quizzes after the deadlines without any penalty.
por Maximiliano B•
Feb 23, 2020
The second course of the specialization is excellent and it provides a solid foundation on sample-based learning methods. The book and the videos complement each other making the learning experience rich and pleasant. The professors explain the content very well and the programming assignments are very interesting to consolidate the knowledge. I had a few issues with the grader and it just returns the score without any message that could help find out what is causing the unexpected behavior. As a suggestion, I would like to suggest that the grader could return any additional information and/or include new unit tests. I am looking forward to begin the next course of the specialization.
May 10, 2020
Very good class. Has much of the same qualities as its predecessor in the specialization. The methods you learn about though are more exciting, since they go beyond the introductory academic stuff that is not really used in production. I can easily see how Q-Learning, SARSA, and DynaQ architectures are usable in the real world.
Programming assignments are also very similar, but just a **little** bit more challenging. Each assignment has just a touch less handholding than the one before it, although there's still a lot of boilerplate included.
Looking forward to the next class!
por Rishi R•
Aug 03, 2020
There are simply no words to explain how well the instructors have constructed and delivered this. The algorithms were beautifully explained ( unlike in the first course where it was missed) and good intuition was given to the subject. The course is amazing in itself.
Yet if permitted I would like to have an addition. It would be way better if the research papers from which these ideas are introduced are also mentioned, also what other future developments have occurred in that direction if that concept is not visited again.
por Mukund C•
Mar 17, 2020
Excellent Course!! Reading the content and making notes ahead of time before watching the lectures is a MUST!!. The graphics/visuals in describing the concepts in the lectures were very good, especially for a visual learning such as myself. However, I wish there were a few more lectures and the lectures were a little - maybe another 3-5 minutes longer and delved into the derivations/concepts - for example - Bellman Equations to Sarsa/Q-learning/TD.
por Sandesh J•
Jun 08, 2020
The course involves several popular Sample-based RL algorithms with relatable graphical visualizations making it an even smoother transition from the previous course. The lecturers have done a great job of explaining the underlying concepts and highlighting the subtleties of the same. Programming assignments were great which solidified the lessons learned.
por Yover M C C•
Apr 22, 2020
Excelente curso, la calidad de las lecturas y tareas de programación son muy buenas, un curso que no solo te ayuda a mejorar tus habilidades matemáticas y de programación en el tema de aprendizaje por refuerzo, sino también a entender parte del proceso de aprendizaje mediante TD. Un curso que se disfruta mucho! Gracias!.
por Alberto H•
Oct 28, 2019
A great step towards the acquisition of basic and medium complexity RL concepts with a nice balance between theory and practice, similar to the first one.
[Note: the course requires mastering the concepts of the first one in the specialization, so don't start here unless you're sure you master its contents.]
por Parsa V•
Jan 06, 2020
This course is perfect.
You will learn everything about sample-based RL. The programming assignments are harder than the previous course, but you will understand all the algorithms better.
These two courses covered part 1 of the book, and you will build a strong foundation of RL for the future.
por Surya K S•
Apr 12, 2020
One of the more technically challenging courses I've done. Extremely fulfilling, a very good course to go along with the Book - "Reinforcement Learning, An Introduction". The assignments are very engaging, same with the videos, concise and to the point. The forums were incredibly useful.
por Dinh-Son V•
Jul 19, 2020
Excellent course. The amount of information is suited for RL enthusiast. The intuition behind the equation are well introduced. The exercises are challenging, yet interesting. It would have been more enriching to introduce examples not only from the textbook but from other materials.
por Mark J•
Sep 23, 2019
In my opinion, this course strikes a comfortable balance between theory and practice. It is, essentially, a walk-through of the textbook by Sutton and Barto entitled, appropriately enough, 'Reinforcement Learning'. Sutton's appearances in some of the videos are an added treat.
por Damian K•
Oct 05, 2019
Great balance between theory and demonstration of how all techniques works. Exercises are prepared so it is possible to focus on core part of concepts. And if you will you can take deep dive into exercise and how experiments are designed. Very recommended course.
por Yoel S•
Apr 19, 2020
Interesting topic, medium-advanced material, loved the programming assignments (despite technical difficulties with submissions), the textbook is excellent, and the online course is well organized, balanced, and well presented. Thank you to the whole team!
por Majd W•
Dec 06, 2019
One of the amazing things this specialization stands out in is that it is based on a textbook. if you read from it and watch the lectures, you will have a very good understanding of the material. Also, the programming assignments are very beneficial.
por Jesse W•
May 14, 2020
This is an excellent course in reinforcement learning. They provide a PDF for a textbook which is very clear and readable, and the lectures do a great job at reinforcing the concepts. The programming assignments are pretty interesting as well.