I think the videos and teaching are great. However, this class is somewhat hard with the math and one can easily get stuck with some of the algorithm problems. This class really needs an ongoing monitor/mentor in the forums to help guide you through the class. Also, sometimes, even when you get the right answer for the quiz, it can be difficult to ascertain whether you actually understand the concept. I docked one star for the lack of ability to get help.

Generally, this course is great, and it focuses on some core theories of algorithms in Computer Science.

Personally, I think the tricky part is the analysis of the algorithms which requires some advanced math knowledge and a lot of patience.

To be honest, though I have finished this course, there's still a must for me to review the whole course later. Also, I need to implement all the algorithms again in both java and python I guess :)

Good subject to take, however, the rhythm in my opinion is quite fast, and less practical example was given to connect with our real life, the teacher is nice, except for too fluently speaking LOL, I am not a native English speaker, thus I have to reduce the speed of the video, but then, I stepped into sleepy soon, even X 0.75 speed is crazy hypnosis technique. LOL, anyway, those just my own thinking and thanks to the teacher.

This course is very good! Every week your are given a programming assignment in wich you have to code some classical algorithms in the language of your preference. Some exercises are difficult to do, but search for help on the forum. The only bad point is that the teacher talks too fast,a lot of time I had too look for better explanations. It's difficul to follow Tim's rithm.

The discussion forum is basically dead.If you ask a question, you will probably get an answer in two months.The programming assignment is not as well-designed and challenging as the Rice and Princeton algorithm specialization. There is no autograder. You just need to enter the output of the programming assignment. Nevertheless, it takes a thorough and rigorous approach.

The instructor offers me a very clear explanation on different algorithm designs. The assignments are also thought-provoking and is able to stimulate your brain.

One thing for improvement is the sufficiency of algorithm exercise. It seems the algorithm exercise the course offers is not enough for those who would like to pursue higher challenge in algorithm puzzles.

Good introductory course: allows to relatively quickly go through the topic without getting stuck in too much detail; hands on assignments are nice and useful. The slides I feel could be further improved to (i) aid rapid understanding, (ii) be more helpful in problem solving and (iii) have a few more maps back to the bigger picture.

This was a good course, but it is not for people who want to get work done using algorithms. It is pretty math heavy and requires ample amount of dedication and understanding. Some high standard videos like the ones on Graph Theory was not very well explained, I had to see some youtube videos to get a nice understanding about them.

I thought the course was well instructed, Tim is a good professor and doesn't give up too many of the answers. I found the probability section needing more review as I didn't come into the course with a statistics background, and I felt that hurt my full comprehension of the material. Other than that, awesome course.

I really like this course and think that the course is very helpful for me as a non-cs major student to learn more about algorithms.

However, I found it hard to find answers to the quiz and the questions. I tried in the forum but in vain. Might be an improvement of the Coursera system and organization?

Perfect start for a NOOB, all algorithms are explained in a detailed way. Only draw back i felt which can be addressed in further version is to include few programmatic assignments, so that developers can relate how the algorithm is translated from mathematical equation to running code.

Sincerely speaking, the lecture is too coarse. It will be more help, if there are more details in lecture. But not only in videos. It is quite waste of time by watching videos one by one. However, by finish this course, I have regained basic algorithm knowledge learned in college.

I took this course to understand more the approach of problem solving and less the mathematical analysis. To understand why the things the way they are , Its sufficient to understand conceptual analysis, rather than mathematical analysis , at least for me.

The course is awesome and explained in details of every topic. However, watching the videos alone is not enough and in my opinion, read the book that the course recommended or look on the internet for relevant reference to support your learning.

A little too much math than what was anticipated, I would have preferred more of why did the CS choose a divide and conquer approach than proofs. The professor talks faster than I can take notes, it's great that we can stop and rewind.

Yea i think it's good. However, some of the proofs didn't 100% make sense to me and I don't prefer sloppy proofs. I'd like more concrete walkthrough of the proofs. I know that's hard for course that has so much content packed into it.

It is the best course for the above algorithms that I have seen till date.The pace and problems are just perfect.It produces interest in us to learn more.Atlast the course is not that tough nor that easy it is just amazing.

The lecturer explains everything very clearly. All materials are interesting but the assignments are not well-prepared and quite little :( I don't think they can assess learner's understanding and knowledge well enough

It is a great course, but the person needs to be determined to complete the course, and you will also have to refer to a lot of external materials... Tim tried to make the course as interesting as possible...

A bit too heavy on the probability and mathematical proof side, otherwise I learned a lot about divide and conquer algorithms and minimum cut as well as the Master Method for algorithm analysis.

As someone with only (UK) high school level maths I just about managed to follow this. I am still confused by logarithms. I guess I should go and read the maths for computer science resource.

I would like a better balance workload from week to week. In my experience it increase every week, so last week I was in a rush, not even being able to go through the optional material.

It would be great if lectures and slides would be with better design and to make and record new slides and lectures. Because these lectures seems too old. Everything else is great.

understand that this is intended to be cross code language information, but would also be nice to see examples of non-pseudo code and implemented into at least one language

Great course for who is seeking to learn new algorithms and their analysis specially the randomized algorithm. but its videos are kind of long compered to other courses.