Chevron Left
Algorithms on Graphs(으)로 돌아가기

캘리포니아 샌디에고 대학교의 Algorithms on Graphs 학습자 리뷰 및 피드백

1,687개의 평가
276개의 리뷰

강좌 소개

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. In this 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....

최상위 리뷰


Jul 01, 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.


Oct 07, 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.

필터링 기준:

Algorithms on Graphs의 267개 리뷰 중 176~200

교육 기관: Elvis Č

Oct 18, 2019

Superb course!

교육 기관: Adithya u

May 11, 2020

A Nice course

교육 기관: Richard C

Mar 07, 2020

Great course.

교육 기관: Ivan G

Jul 21, 2017

Great course!

교육 기관: Lie C

Jun 29, 2018

good courses

교육 기관: pengwei

Dec 12, 2016

great course

교육 기관: Neeraj S A

Oct 02, 2016

Great Course

교육 기관: Weidong X

Jul 14, 2016

Good course!

교육 기관: Manish S

Jan 17, 2020

its awesome

교육 기관: uddeshya p

Sep 02, 2019

its awesome

교육 기관: Carlos D R S

Jul 23, 2017

Está perro.

교육 기관: Đặng T S

Dec 12, 2016

nice course

교육 기관: Om P

Jul 13, 2017

Awesome !!

교육 기관: Prabhu N S

Jul 14, 2020


교육 기관: nguyen7thai

Sep 19, 2016

Very good

교육 기관: Sai C

Jun 15, 2020

great !!

교육 기관: Huimeng Z

May 13, 2020


교육 기관: Chen X

Mar 13, 2019


교육 기관: Andrea Q

Sep 17, 2017


교육 기관: Tushar G

Jul 18, 2016


교육 기관: D A

Apr 19, 2020


교육 기관: RICARDO G

May 24, 2017


교육 기관: Anup V

Nov 14, 2016

The course was awesome but the "Algorithms on Graphs" course the month after has some ridiculous extras. Since the course hereafter will have additions related to how Graphs are used in the real world today - I have to give this current course 4 stars. I can't comment on the next course but I think talking about how graphs are used in RL is immeasurable. Good Luck. I do hope you give this course a chance if you're interested in Graphs or looking for a refresher like I was.

교육 기관: Ayush C

Aug 03, 2020

This course introduced me to graphs, and various algorithms on graphs, which are very useful and interesting. It is a great course to understand various graph algorithms. Although the number of questions in programming assignments in this course were lesser than in previous courses of the specialization. Nonetheless, it completely explains various graph algorithms lucidly and teaches how to apply them with interesting questions in assignments.

교육 기관: Ritik

Jul 02, 2019

This a great course for revising algorithms on graph. Assignments are also good for understanding problems better. You can do this course in a day or two . It is that much understandable. Also you can do submission on any programming languages from c++, python, java which is rare on any other course on Coursera. But if you want to learn from scratch then please also refer external reference for algorithms.