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.
This course is part of the Data Structures and Algorithms Specialization
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Data Structures and Algorithms SpecializationUniversity of California San DiegoAbout this Course
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Course 3 of 6 in the
Intermediate Level
Approx. 55 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessSkills you will gain
- Graph Theory
- Graphs
- Graph Algorithms
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 3 of 6 in the
Intermediate Level
Approx. 55 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Could your company benefit from training employees on in-demand skills?
Try Coursera for Business
Offered by
University of California San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Syllabus - What you will learn from this course
5 hours to complete
Decomposition of Graphs 1
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 hot in Facebook, you're going to work with graphs and algorithms on graphs. In this module, you will learn ways to represent a graph as well as basic algorithms for decomposing graphs into parts. In the programming assignment of this module, you will apply the algorithms that you’ve learned to implement efficient programs for exploring mazes, analyzing Computer Science curriculum, and analyzing road networks. In the first week of the module, we focus on undirected graphs.
5 hours to complete
5 videos (Total 43 min), 5 readings, 1 quiz
4 hours to complete
Decomposition of Graphs 2
This week we continue to study graph decomposition algorithms, but now for directed graphs.
4 hours to complete
4 videos (Total 36 min), 1 reading, 1 quiz
4 hours to complete
Paths in Graphs 1
In this module you will study algorithms for finding Shortest Paths in Graphs. These algorithms have lots of applications. When you launch a navigation app on your smartphone like Google Maps or Yandex.Navi, it uses these algorithms to find you the fastest route from work to home, from home to school, etc. When you search for airplane tickets, these algorithms are used to find a route with the minimum number of plane changes. Unexpectedly, these algorithms can also be used to determine the optimal way to do currency exchange, sometimes allowing to earh huge profit! We will cover all these applications, and you will learn Breadth-First Search, Dijkstra's Algorithm and Bellman-Ford Algorithm. These algorithms are efficient and lay the foundation for even more efficient algorithms which you will learn and implement in the Shortest Paths Capstone Project to find best routes on real maps of cities and countries, find distances between people in Social Networks. In the end you will be able to find Shortest Paths efficiently in any Graph. This week we will study Breadth-First Search algorithm.
4 hours to complete
8 videos (Total 56 min), 1 reading, 1 quiz
5 hours to complete
Paths in Graphs 2
This week we continue to study Shortest Paths in Graphs. You will learn Dijkstra's Algorithm which can be applied to find the shortest route home from work. You will also learn Bellman-Ford's algorithm which can unexpectedly be applied to choose the optimal way of exchanging currencies. By the end you will be able to find shortest paths efficiently in any Graph.
5 hours to complete
13 videos (Total 90 min), 2 readings, 1 quiz
Reviews
- 5 stars79.12%
- 4 stars16.88%
- 3 stars2.64%
- 2 stars0.83%
- 1 star0.51%
TOP REVIEWS FROM ALGORITHMS ON GRAPHS
by HLSep 28, 2020
The content of the course is good and easy to follow. However, I wish the grader's response provided more helpful information (such as conditions of the failed test).
by ADJun 23, 2020
This course is very well designed, starting from basic concepts and thoroughly covering all Graph relevant Algorithms. A big thank you to all Professors.
by EDApr 15, 2021
This is my favorite course in the specialization, the lectures are really clear and the programming assignments are fun and really help to deeply understand everything
by FYJan 6, 2021
I've wanted to learn about Graphs and the algorithms associated with it for a long time, and I cannot imagine a better course to learn it from. Thank you?
About the Data Structures and Algorithms Specialization
Computer science legend Donald Knuth once said “I don’t understand things unless I try to program them.” We also believe that the best way to learn an algorithm is to program it. However, many excellent books and online courses on algorithms, that excel in introducing algorithmic ideas, have not yet succeeded in teaching you how to implement algorithms, the crucial computer science skill that you have to master at your next job interview. We tried to fill this gap by forming a diverse team of instructors that includes world-leading experts in theoretical and applied algorithms at UCSD (Daniel Kane, Alexander Kulikov, and Pavel Pevzner) and a former software engineer at Google (Neil Rhodes). This unique combination of skills makes this Specialization different from other excellent MOOCs on algorithms that are all developed by theoretical computer scientists. While these MOOCs focus on theory, our Specialization is a mix of algorithmic theory/practice/applications with software engineering. You will learn algorithms by implementing nearly 100 coding problems in a programming language of your choice. To the best of knowledge, no other online course in Algorithms comes close to offering you a wealth of programming challenges (and puzzles!) that you may face at your next job interview. We invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs.
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