I am a researcher and (in past) an instructor in SDP, Randomized and Approximation Algorithms.

There are a few instances, where things are not explained as well as an advanced UG or a starting Grad student would like, e.g., Knapsack got a bit delirious somewhere in between (the "special special" case, which IMHO was not needed.)

Otherwise, I love Claire's enthusiasm, and the joy she finds in delivering the ideas. She is succinct everywhere (to me).

Very good !

This course is awesome. Prof. managed to elaborate the problem and analysis clearly and homework is properly assigned.

Really good course and Professor.

A very synthetic course on the topic.Explanations are of great quality and elegant!

Every algorithms given are analysed on a mathematical point of view.

ENS should enable people to get certificate for this course ! I would prefer

give money to this top institution in theorical science than to the huge private universities

To improve : the commitment of the staff to the forum

The content of the course is good and the lectures even better. However the quizzes and homeworks could use an update or refresh. The forums connected to the course is a ghosttown.

super cool!

Great course!

This class is very clear and easy to understand! Thank you for providing such feast for students!

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I love how this course delves into a very promising advanced research topic in Computational Complexity. It helps me a lot to understand trending publications in the area. Specially that the material is presented in an incremental approach. This way a researcher can live through the evolution of ideas. It is inspiring also in the way one comes up with a partial solution for the special case, and then generalizes with approximation factor that is satisfyingly good. I'm looking forward to more advanced courses in parameterized, streaming or quantum algorithms.

good course, with many examples and explanations

Content of the course is great. However , at time assignments are very difficult to understand. There are probably very few students who take this course at any time , so you dont get much help from forums. TA's and Professor as well have not responded to any of our questions. I dont expect any course to be cakewalk but at least some help need to be provided.

The assignments could be a bit improved (some are less good, I would personally complain about knapsack), but in general it is a great course, as it gives an accessible introduction to approximation algorithms (for NP-hard problems), which is a very relevant topic, as NP-hard problems are everywhere.

At the time of writing (end summer 2016), it is also a unique course for this very relevant topic.

Very interesting, explanations are clear and easy to understand

Lectures and content were great. The theme of the course is to provide insight into the approaches used to investigate approximation algorithms for NP hard problems and the theoretical techniques used to assess the effectiveness of the approximation algorithm against the best answer. The production quality of the lecture videos and slides was high.

The content of the quizzes and assignments was mostly appropriate and well organized. However, the authors appeared to struggle with the platform. At times there were comments such as, you need to enter something in the box but it was not actually being used. Answers to the assignments required using substantial mathematical notation, but LaTex was not enabled in the discussion or text entry boxes (no longer available in the Coursera platform??) so the work around was to upload answers to a bunch of questions as a single PDF document. Flow of the individual modules (lectures, slides, quizzes) was inconsistent, varying from week to week.

This was a relatively easy but well paced introduction to approximation algorithms. I totally enjoyed it.

Excellent!

Excellent advanced course! Not for beginner in computer science, nor for people more interested in applying computer science than in theoretical foundations.

This course covers the basic ground about approximation algorithms and would be very valuable for a practitioner, but seems designed for people who already know the materials and is more theoretical than applied.

Lectures are very abstract --with a description of the problem and a formal description of the solution--, there are few examples with step-by-step tracing of algorithms --that is how the algorithm actually works to solve the problem--, and a significant amount of expertise is assumed --so much so, that you wouldn't need this course. For example, there are questions about "approximation ratio", but it is not explained. This seems like something that is inherent to approximation algorithms, but is only asked in the exams/project, and is not even mentioned in the lectures. Similar issues abound around the course.

Excellent Course! I have learnt a lot about Approximation Algorithms in a short span of time.

Great class, and Professor Claire Mathieu is doing an excellent job!

A really good course for programmers who want to take a bit deeper into CS.

Lectures are well-organized. Some assignments (e.g., Assignment 3, which involves merely understanding an algorithm, rather than proving correctness and approx. ratio) are extraordinarily stupid and somewhat tangential.

Really good course, the material is quite advanced but very well structured and introduced in a very simple way. The assignments were a lot of fun: really enjoyed the peer-graded assignments where I needed to write short proofs, much more useful than regular multiple-choice answers. Looking forward to the next course!