Chevron Left
返回到 Divide and Conquer, Sorting and Searching, and Randomized Algorithms

學生對 斯坦福大学 提供的 Divide and Conquer, Sorting and Searching, and Randomized Algorithms 的評價和反饋

4.8
3,215 個評分
572 個審閱

課程概述

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts)....

熱門審閱

KS

Sep 14, 2018

Well researched. Topics covered well, with walkthrough for exam.le cases for each new introduced algorithm. Great experience, learned a lot of important algorithms and algorithmic thinking practices.

CV

Jun 11, 2017

A really exciting and challenging course. Loved the way the instructor explained everything with so much detail and precision. Definitely looking forward to the next course in the specialization.

篩選依據:

76 - Divide and Conquer, Sorting and Searching, and Randomized Algorithms 的 100 個評論(共 554 個)

創建者 Sushruth

Aug 19, 2018

Awesome course.

創建者 YX L

Aug 19, 2018

Very helpful, informative course. The way professor explain the concept is quite straightforward and easy to understand. there are also plenty of exercises to make sure you understand all the details in algorithm.

創建者 Steve J

Sep 20, 2018

I found this course to be an ideal mix of abstract theory and practical application. Professor Roughgarden is quite adept at presenting in depth analyses of algorithms in a way that does not shy away from formal mathematics but also does not require a degree in mathematics to understand. For me, whose prior math coursework was mainly focused on areas of math not as prevalent in computer science as other in disciplines (e.g. calculus vs. discrete math), Professor Roughgarden's approach is ideal and opened up the door to a much deeper understanding of algorithms than I've acquired on my own over a multi-decade career in programming.

Highly recommend this course for anyone who, like me, has a lot of experience with programming, but no formal training on algorithms.

創建者 Yiquan L

Oct 08, 2018

According to completed assignment, I think I get a lot.

創建者 Ivan L

Oct 23, 2018

it is really great and so so simple as title sounds

創建者 Nikhil N P

Oct 27, 2018

loved one

創建者 Babak M S

Oct 31, 2018

Great course and great instructor.

創建者 Srivatsan K I

Aug 31, 2018

good organised modules to learn algorithm

創建者 黃正豪

Aug 31, 2018

Quizzes and assignments could be challenging but it worth it.

創建者 Nikola G

Jul 15, 2018

Really strong introduction to algorithms!

創建者 kwadwo a

Jul 17, 2018

Challenging and enlightening

創建者 Yiming Z

Jul 17, 2018

A very good course! Just feel excited and motivated to learn algorithms! Now I am determined to be a computer science major in college.

創建者 Chi M

Jul 11, 2018

The lectures gave me very good direction to study algorithms. Thanks!

創建者 Abhishek C

Jul 10, 2018

quite good course

創建者 Sriram V

Mar 06, 2018

Outstanding course. Thoroughly enjoyed it!

創建者 Tyantov

Nov 17, 2017

Very nice course, thanks Tim!

創建者 YANG Y

Jun 19, 2017

The best course I've taken on any MOOC by far. I'm satisfied with both its depth and professor's intuitive teaching. Assignments are also challenging, deeply connected to the material. Strongly recommend to any like me who is new to algorithms.

創建者 Rafael E

Jun 08, 2018

An excellent intro to analysis of algorithms!

創建者 John W

Jul 08, 2017

Really enjoyed watching the lectures and Prof Roughgarden's explanations. He did a good job diving just deep enough into the math without losing me.

創建者 ryan

Sep 28, 2017

awesome!

創建者 Dima T

Mar 13, 2017

I like this course a lot. Going to learn everything in the specialization.

創建者 Mohammad N

Nov 20, 2016

This is a great course for who doesn't have a computer science background!

創建者 Apostolos S

Nov 06, 2016

Great course with interesting assignments.

創建者 Bhaskar V

Sep 11, 2017

Great refresher and good starting point for Algorithm Specialization

創建者 jinesh p

May 08, 2017

It was really nice learning experience.