If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect set of computers into a network or efficient algorithm to automatically find communities and opinion leaders in Facebook, you're going to work with graphs and algorithms on graphs. In this course, you will first learn what a graph is and what are some of the most important properties. Then you'll learn several ways to traverse graphs and how you can do useful things while traversing the graph in some order. We will then talk about shortest paths algorithms — from the basic ones to those which open door for 1000000 times faster algorithms used in Google Maps and other navigational services. You will use these algorithms if you choose to work on our Fast Shortest Routes industrial capstone project. We will finish with minimum spanning trees which are used to plan road, telephone and computer networks and also find applications in clustering and approximate algorithms. Do you have technical problems? Write to us: coursera@hse.ru...

Perfect as previous courses of the specialization. Just basic graph algorithms were given. I'm inclined to believe, it was introduction to algorithms on graphs.

Great course, would have been better, if authors added more assignments and material to study as graphs have so many applications. Anyways, I do believe that motivated learners will go ahead and find more challenges for themselves. As always, thanks to all the instructors, keep up the good work!

I have finished the specialization. This course is mostly useful though challenging. I wish there were less overly theoretical lectures and more practical examples and assignments instead. Textbooks already have theory.

Very good explanations

Good sessions and assignments.

Lectures were very clear and assignments were really helpful for me to understand gist of each algorithms. This course, however, only covers 1. Basic concepts of Graph, 2. Shortest Path, and 3. Minimum Spanning Tree which doesn’t seem to be rich.

With more diverse and interesting problems associated with Graph included, I strongly believe that students will get much from this course.

Thank you

Good Course material and Assignment.

I never a reply when i ask a question on the discussion forum, kindly improve this, otherwise the course was great.

Great

This course is easier than the previous three, but will help in gaining basic to intermediate knowledge on graphs.

Was very informative course. Learned a lot stuff.

Good course , nice assignments , a little bit more of explanation might be helpful for beginners

Amazing course

Very useful course with clear presentation of material. Removing 1 star for lack of recent feedback, even if missing link to programming assignment's problem statement file is reported. One shouldn't have to fish around in forums to find it!

this course provides the simplist way to explain algorithms, but more exercises may be helpful to improve understanding of topics.

The explanation of lecturer is not good as expected. Overall it is good.

This a great course for revising algorithms on graph. Assignments are also good for understanding problems better. You can do this course in a day or two . It is that much understandable. Also you can do submission on any programming languages from c++, python, java which is rare on any other course on Coursera. But if you want to learn from scratch then please also refer external reference for algorithms.

Great course for learning or revisiting the concepts of algorithms on graphs. Definitely recommend it.

The lecture is pretty much scripted from the DPV book...

Всё хорошо, но есть задачи, где (например) формат ввода накладывает ограничения на максимальную эффективность. Например, нет никакого смысла писать DSU для Крускала, если только ввод данных займёт n^2

For those who passed previous two courses in this Specialization, this course will probably be easy to pass, even if you aim at 100%. I liked the programming assignments, did not like videos that much. Used to find myself watching different explanations from the Web. On the other hand, if you want to absorb all stuff presented here, this course is not too easy IMHO.

I must say I feel disappointed especially when the whole Data Structures and Algorithms series take this course as the selling point ( "you'll learn how to compute the fastest route between New York and Mountain View thousands of times faster than classic algorithms and close to those used in Google Maps", blablabla), but it turns out to be the least challenging course with only elementary introduction to the big topic. Perhaps the preparing time for this course is too short? I still miss the teaching style and assignment design of the first course of the series though. It would seem to be unwise to pay for the following courses if this continues on.

(FYI I was the among the first ones who take this series, and I have got 100% grade for each course ever since then.)

programming assignments were too difficult

Far too easy

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