Chevron Left
Divide and Conquer, Sorting and Searching, and Randomized Algorithms(으)로 돌아가기

스탠퍼드 대학교의 Divide and Conquer, Sorting and Searching, and Randomized Algorithms 학습자 리뷰 및 피드백

4.8
3,133개의 평가
555개의 리뷰

강좌 소개

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)....

최상위 리뷰

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.

필터링 기준:

Divide and Conquer, Sorting and Searching, and Randomized Algorithms의 539개 리뷰 중 226~250

교육 기관: Vaasu S

Aug 05, 2017

Beautiful. Very good teaching. Good quizzes.

교육 기관: Khan M A

May 22, 2017

Thanks so much

교육 기관: Abhishek V

Jan 03, 2017

Very good review of divide and conquer algorithms, however, I only recommend for those who are willing to put in the hard work as I found it challenging.

교육 기관: Nagaraj G

Nov 17, 2016

very challenging fast-paced course

교육 기관: Nikolaos E

Nov 07, 2016

Personally, I would recommend this course to anyone who really wants to learn how things work in that sort of algorithms. I found the assignments a little difficult, but also extremely helpful.

교육 기관: Frank Z

Apr 22, 2018

Extremely great teach!!!

교육 기관: Fabien T

Jun 02, 2017

Outstanding! I've learned a lot during the past 5 weeks spent on the videos, quizzes and assignments. Thanks a lot to Tim Roughgarden for putting together this excellent course and to the Coursera team for hosting it.

교육 기관: Ankit A

May 24, 2018

An in-depth course, that one must take!

교육 기관: Amir E E

Jul 06, 2017

Instructor is great!

교육 기관: Lluis T

Dec 15, 2017

Great course! It was very well planned an oriented for experimented programmers that need that pinch of salt needed to get the best in their codes. I strongly recommend to use TDD in the development of the programming practices.

A resume?: it's a MUST.

교육 기관: Solomon B

Mar 11, 2017

Excellent course. The statistical analysis was a little too fast and overwhelming towards the end but overall I learned a lot.

교육 기관: sysucx

Jan 05, 2017

数学系的学生修这门课感觉很带劲~

교육 기관: Vikas D

Dec 16, 2016

Awesome,right now I know why algorithms are most important..!!

교육 기관: Tushar

Jun 11, 2017

Very nice and structured course , with an intention to imbibe the "thinkness" in students for algorithms

교육 기관: Sangeet M D

May 31, 2017

I always had my doubt on whether to choose which course on Algorithm in coursera, The Princeton one or the Stanford one. Though I can weight one above the other, but the flow is which the Stanford one proceed is the best for any lower Intermediate level student to wants to learn the upper fundamentals of Algorithm Analysis.

교육 기관: Zikang Z

Jun 28, 2017

Excellent courses

교육 기관: Jamie J S

Jan 01, 2017

I'm so glad that I've taken this course. This is really fantastic.

교육 기관: Ankit A

Nov 01, 2016

This is great course

교육 기관: Isaac S R

May 12, 2018

Outstanding introduction to algorithms with great practice problems and quizzes

교육 기관: Yue W

Sep 05, 2017

Amazing!!

교육 기관: Andy

Jul 23, 2017

An excellent course for beginners looking to grasp fundamental concepts of algorithms!! Professor Roughgarden was brilliantly lucid in his explanations and the assignments and evaluations were helpful in assimilating the concepts covered. It was pleasure to take this course.

교육 기관: Gireesh N

May 27, 2017

Awesome!

교육 기관: Boyang W

Apr 02, 2018

Very good course

교육 기관: Yixian H

Mar 11, 2018

Though final coding assignment has a little difficult, it's a definitely fantastic course!

교육 기관: Faiz R

Mar 16, 2017

Very good course in algorithms. I bought the book to help me understand but the lectures make it way easier and thus much more fun to understand the analysis. Looking forward to complete the spec