Algorithms on Graphs
Data Structures and Algorithms,
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 a 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 online 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.
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| Rating | 4.4★ based on 203 ratings |
|---|---|
| Length | 7 weeks |
| Effort | 5 weeks of study, 3-4 hours/week |
| Starts | Jun 26 (48 weeks ago) |
| Cost | $79 |
| From | University of California San Diego, National Research University Higher School of Economics, HSE University via Coursera |
| Instructors | Alexander S. Kulikov, Michael Levin, Daniel M Kane, Neil Rhodes |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science Algorithms Software Development |
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What people are saying
very good
Very good course with clear lectures and interesting programming assignments Very good.
Very good course.
The instructors are very good and the assignments are superb.
The lectures and materials were very good.
Very good explanations The course was awesome but the "Algorithms on Graphs" course the month after has some ridiculous extras.
Very good Great Course.
Good Questions and very good Test Cases.
Very good explanations.
thanks for providing the amazing courses Optional part is very good, gives a lot of practical problems to solve.
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graph algorithms
Amazing class that helped me understand graph algorithms.
Just basic graph algorithms were given.
Starts with gentle introduction to graphs followed by various traversal schemes.Shortest path problems and minimum spanning tree problems are covered in great detail.Advanced graph algorithms such as A* are also covered.Very well organized course.
This sets a concrete foundation to Graph Algorithms though it might be a bit steep for a complete starter.
Incredible collection of graph algorithms.
I am new on graph algorithms and this course totally mesmerized me.
All basic graph algorithms are covered.
Great Course to understand the graph algorithms and hone the skills to solve the Graph Problems.
Great explanation of basic graph algorithms (week 1-5).
Great Course to learn fundamentals of Graph Algorithms.
good courses Awesome course that gives an introduction to basic and some advanced graph algorithms.
Really good explanations and very useful and, I believe, commonly used graph algorithms.
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data structures
As a suggestion, i would like to say that add some extra contents on the data structures which is to be used in the algorithm.
Even though I am not a programmer and didn't do the other courses in the specializations, I could still go through this course with only a small amount of personal research on data structures (which are covered in previous courses of the specialization).
I started this one right after completing data structures and found it particularly interesting as graph problems seem to pop up everywhere in our modern, networked world.Compared to the data structures course this definitely felt easier, however this may be down to me being more comfortable with my chosen language as well as with the overall process and structure of the assignments.
Nevertheless there are some fun problems here that have connections to problems in the "real" world.As a side note, I recommend doing the data structures course before this one, as some of the algorithms discussed rely on data structures, so understanding them and better yet having them implemented already will help a lot with focusing on the new material and passing the assignments.Thanks again all the teachers for the great course!
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.
Why don't you put it in the Data Structures course?
Would recommend this to anyone working as developer who does not have formal education in data structures and algorithms.
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previous courses
But we need to religiously follow the videos and materials Perfect as previous courses of the specialization.
Maybe a bit easier than the previous ones in this specialization, or maybe it's just because I started using python(compared to java and c in previous courses).
This course took a bit more time than previous courses of the specialisation.
Content is as good as two previous courses from specialization.
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about graphs
All you always wanted to know about graphs are here.
Anyone who wants to understand a bit more about graphs and the corresponding algorithms should take up this course.
One of the rare courses that teach everything about Graphs!
Learned a lot about graphs, and I thought it was super awesome.
Learnt a lot about graphs, traversing, running time, shortest paths, minimum spanning trees etc., Most of all the problem statement gradually became challenging and we had to actually model the problem statement to fit the algorithm.
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programming assignments
I liked the programming assignments, did not like videos that much.
I wish the edge cases for some of the programming assignments had some more discussions.
programming assignments were too difficult Great course for learning or revisiting the concepts of algorithms on graphs.
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| Rating | 4.4★ based on 203 ratings |
|---|---|
| Length | 7 weeks |
| Effort | 5 weeks of study, 3-4 hours/week |
| Starts | Jun 26 (48 weeks ago) |
| Cost | $79 |
| From | University of California San Diego, National Research University Higher School of Economics, HSE University via Coursera |
| Instructors | Alexander S. Kulikov, Michael Levin, Daniel M Kane, Neil Rhodes |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming |
| Tags | Computer Science Algorithms Software Development |
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