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.

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.

It would be good to have more simple examples, like how theoretical results can be applied, with exact numbers and not with abstract n, a, k, b, j after we prove them.

Kindly make it more simpler by adding more practise problems so that solving problems become more easier during the test and thereby to gain more knowledge on the same

It would be better to have more test cases linked to programming assengments. Hoppefully, there is a github branch with that already... but better to merge it to here

High rank because the instructor really makes the material come alive. Not a 5-star since I wish there was more supporting materials to accompany the course. Thanks!

Good if you want to be a researcher or follow your career on algorithms but not so good if you want to learn using ds and algos fast to crack technical interviews.

great course but it would be better if you ask students to submit their code and give limits and various test cases like an actual programming contest.