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.
Este curso faz parte do Programa de cursos integrados Estruturas de dados e algoritmos
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oferecido por
Programa de cursos integrados Estruturas de dados e algoritmosUniversidade da Califórnia, San DiegoInformações sobre o curso
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Prazos flexíveis
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Certificados compartilháveis
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Nível intermediário
Aprox. 55 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
Habilidades que você terá
- Graph Theory
- Graphs
- Graph Algorithms
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Nível intermediário
Aprox. 55 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Italiano, Vietnamita, Alemão, Russo, Inglês, Espanhol
oferecido por
Universidade da Califórnia, 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.
Programa - O que você aprenderá com este curso
5 horas para concluir
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 horas para concluir
5 vídeos (Total 43 mín.), 5 leituras, 1 teste
4 horas para concluir
Decomposition of Graphs 2
This week we continue to study graph decomposition algorithms, but now for directed graphs.
4 horas para concluir
4 vídeos (Total 36 mín.), 1 leitura, 1 teste
4 horas para concluir
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 horas para concluir
8 vídeos (Total 56 mín.), 1 leitura, 1 teste
5 horas para concluir
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 horas para concluir
13 vídeos (Total 90 mín.), 2 leituras, 1 teste
Avaliações
- 5 stars79,17%
- 4 stars16,79%
- 3 stars2,66%
- 2 stars0,84%
- 1 star0,51%
Principais avaliações do ALGORITHMS ON GRAPHS
por FS17 de set de 2020
This course helps me to a better understanding of Graph Theory. The exercise was a little bit difficult but it can help me to gain more knowledge to solve these problem.
por TL14 de dez de 2020
Good course. Really enjoyed attending Alexander Kulikov's lectures throughout the entire specialization. His lessons are really easy to understand with lots of visualizations.
por SK23 de abr de 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.
por HL28 de set de 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).
Sobre Programa de cursos integrados Estruturas de dados e algoritmos
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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