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.
Об этом курсе
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.
- 5 stars79,11 %
- 4 stars16,84 %
- 3 stars2,67 %
- 2 stars0,84 %
- 1 star0,51 %
Лучшие отзывы о курсе ALGORITHMS ON GRAPHS
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).
Explanations were as clear as possible. The problem sets were nice enough. It would be excellent if some advanced topics (like Flow) could be added to this particular course.
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?
I got a lot of knowledege about the algorithms on graphs. The assignments will be a little difficulte for beginner of computer programming but for others this course is worth to join.
Специализация Структуры и алгоритмы данных: общие сведения
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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