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.
Этот курс входит в специализацию ''Специализация Структуры и алгоритмы данных'
Algorithms on Graphs
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Калифорнийский университет в Сан-Диего
Национальный исследовательский университет "Высшая школа экономики"
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Курс 3 из 6 в программе
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Прибл. 55 часа на выполнение
Английский
Субтитры: Английский
Приобретаемые навыки
Graph TheoryGraphsGraph Algorithms
Карьерные результаты учащихся
30%
начал новую карьеру, пройдя эти курсы
24%
получил значимые преимущества в карьере благодаря этому курсу
15%
стал больше зарабатывать или получил повышение
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 3 из 6 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень
Прибл. 55 часа на выполнение
Английский
Субтитры: Английский
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Калифорнийский университет в Сан-Диего
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.
Национальный исследовательский университет "Высшая школа экономики"
National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more.
Программа курса: что вы изучите
4 ч. на завершение
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.
4 ч. на завершение
5 видео ((всего 43 мин.)), 3 материалов для самостоятельного изучения, 1 тест
5 видео
Graph Basics4мин
Representing Graphs9мин
Exploring Graphs14мин
Connectivity5мин
Previsit and Postvisit Orderings7мин
3 материала для самостоятельного изучения
Welcome10мин
Slides and External References10мин
Slides and External References10мин
4 ч. на завершение
Decomposition of Graphs 2
This week we continue to study graph decomposition algorithms, but now for directed graphs.
4 ч. на завершение
4 видео ((всего 36 мин.)), 1 материал для самостоятельного изучения, 1 тест
4 видео
Topological Sort9мин
Strongly Connected Components7мин
Computing Strongly Connected Components10мин
1 материал для самостоятельного изучения
Slides and External References10мин
4 ч. на завершение
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 ч. на завершение
8 видео ((всего 55 мин.)), 1 материал для самостоятельного изучения, 1 тест
8 видео
Breadth-First Search7мин
Breadth-First Search (continued)6мин
Implementation and Analysis9мин
Proof of Correctness7мин
Proof of Correctness (continued)5мин
Shortest-Path Tree6мин
Reconstructing the Shortest Path3мин
1 материал для самостоятельного изучения
Slides and External References10мин
5 ч. на завершение
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 ч. на завершение
12 видео ((всего 86 мин.)), 2 материалов для самостоятельного изучения, 1 тест
12 видео
Fastest Route6мин
Naive Algorithm10мин
Dijkstra's Algorithm: Intuition and Example7мин
Dijkstra's Algorithm: Implementation3мин
Dijkstra's Algorithm: Proof of Correctness4мин
Dijkstra's Algorithm: Running Time7мин
Currency Exchange6мин
Currency Exchange: Reduction to Shortest Paths8мин
Bellman-Ford Algorithm6мин
Bellman-Ford Algorithm: Proof of Correctness6мин
Negative Cycles7мин
Infinite Arbitrage10мин
2 материала для самостоятельного изучения
Slides and External References10мин
Slides and External References10мин
Рецензии
Лучшие отзывы о курсе ALGORITHMS ON GRAPHS
от партнера CSJun 30, 2019
Excellent Course for anyone looking to expertise Graph Algorithm. Professor's explained each problem and algorithm in a very easy to learn approach. Grades are tough and yet func to get challenged.
от партнера CCOct 6, 2018
Good balance between theory and practice. The assignments are well thought to measure the understanding of videos, which I had to watch many times to grasp the hidden tips from the instructor.
от партнера MMMar 28, 2020
An awesome overview of the graph algorithms. Some assignments are really challenging, but luckily forums are a great place where people have already faced them. A definitive recommendation!
от партнера CMMar 6, 2017
Overall good course, programming tasks are fun!\n\nHowever, some of the video lectures are only of average quality. Accent of the TA is sometimes confusing (fyi I'm not a native speaker).
от партнера SKApr 23, 2018
This course is very much helpful for the graph beginners. 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.
от партнера GSDec 2, 2019
very well planned course and fairly challenging assignments. Would recommend this to anyone working as developer who does not have formal education in data structures and algorithms.
от партнера DPNov 7, 2019
Awesome course! Learned a lot about graphs, and I thought it was super awesome. One recommendation is to make the proof videos more engaging, but otherwise, the course was perfect!
от партнера ZHJan 5, 2017
Very interesting and well presented course. I particularly wanted to learn more on graphs and this helped me get not only a basic but a more advanced understanding.
от партнера ANFeb 27, 2017
Fairly good course. I wish the edge cases for some of the programming assignments had some more discussions. Needed some sifting through the forums while stuck.
от партнера NGJun 27, 2019
Loved the explanations and proofs. They are so explicitly told. And the discussion forum for you well assorted problems in assignment is really helpful.
от партнера EMSep 22, 2017
Great!\n\nHard concepts explained clearly and in depth, in the same fashion as the previous two courses (Algo Toolbox and Data Structure).\n\nGood job!
от партнера DSApr 5, 2020
So far my favorite course of the specialization. The learning path is really smooth and the lectures and programming assignments are to the point.
Специализация Структуры и алгоритмы данных: общие сведения
This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it comes to learning algorithms...or anything else in computer science! For each algorithm you develop and implement, we designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming. The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco (1000 times faster than the standard shortest path algorithms!) Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.
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