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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

4,831개의 평가
937개의 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


2018년 9월 13일

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.


2020년 5월 26일

Thank you for teaching me this course. I learned a lot of new things, including Divide-and-Conquer, MergeSort, QuickSort, and Randomization Algorithms, along with proof for their asymptotic runtime

필터링 기준:

Divide and Conquer, Sorting and Searching, and Randomized Algorithms의 922개 리뷰 중 801~825

교육 기관: Norman W

2018년 6월 24일

Yea i think it's good. However, some of the proofs didn't 100% make sense to me and I don't prefer sloppy proofs. I'd like more concrete walkthrough of the proofs. I know that's hard for course that has so much content packed into it.

교육 기관: Dinh C T

2021년 5월 22일

Mathematical analysis and induction to divide and conquer strategy of the professor are really attractive. Base of a programming language to implement and test the algorithm during the lecture reading is highly recommended.

교육 기관: Pranav K

2020년 4월 17일

It is the best course for the above algorithms that I have seen till date.The pace and problems are just perfect.It produces interest in us to learn more.Atlast the course is not that tough nor that easy it is just amazing.

교육 기관: Khánh N

2018년 8월 23일

The lecturer explains everything very clearly. All materials are interesting but the assignments are not well-prepared and quite little :( I don't think they can assess learner's understanding and knowledge well enough

교육 기관: Rishabh P

2020년 3월 31일

It is a great course, but the person needs to be determined to complete the course, and you will also have to refer to a lot of external materials... Tim tried to make the course as interesting as possible...

교육 기관: ChitHtun N

2022년 3월 21일

Since I am relatively new to computer science, this course is a little bit hard.

But, overall it's ok and the course also mentioned the similar material is taken by sophomores, juniors and seniors.

교육 기관: Ali I C

2020년 1월 4일

A bit too heavy on the probability and mathematical proof side, otherwise I learned a lot about divide and conquer algorithms and minimum cut as well as the Master Method for algorithm analysis.

교육 기관: Joe

2017년 4월 29일

As someone with only (UK) high school level maths I just about managed to follow this. I am still confused by logarithms. I guess I should go and read the maths for computer science resource.

교육 기관: Gonzalo E

2018년 4월 8일

I would like a better balance workload from week to week. In my experience it increase every week, so last week I was in a rush, not even being able to go through the optional material.

교육 기관: Emin E

2018년 1월 27일

It would be great if lectures and slides would be with better design and to make and record new slides and lectures. Because these lectures seems too old. Everything else is great.

교육 기관: Pablo J

2019년 8월 28일

understand that this is intended to be cross code language information, but would also be nice to see examples of non-pseudo code and implemented into at least one language

교육 기관: Xiaoliu W

2020년 7월 12일

Nice material. Wish the instructor can go over some part of the material a little slower. Also it would be nice if the solution of the optional questions can be provided.

교육 기관: Ahmad B E

2017년 5월 9일

Great course for who is seeking to learn new algorithms and their analysis specially the randomized algorithm. but its videos are kind of long compered to other courses.

교육 기관: Ivan C

2019년 11월 13일

It would be good to have more simple examples, like how theoretical results can be applied, with exact numbers and not with abstract n, a, k, b, j after we prove them.

교육 기관: Madhumala J

2019년 3월 27일

Kindly make it more simpler by adding more practise problems so that solving problems become more easier during the test and thereby to gain more knowledge on the same

교육 기관: dmitriy m

2018년 4월 28일

It would be better to have more test cases linked to programming assengments. Hoppefully, there is a github branch with that already... but better to merge it to here

교육 기관: Justin S

2019년 1월 29일

High rank because the instructor really makes the material come alive. Not a 5-star since I wish there was more supporting materials to accompany the course. Thanks!

교육 기관: Mayank K

2020년 1월 16일

Good if you want to be a researcher or follow your career on algorithms but not so good if you want to learn using ds and algos fast to crack technical interviews.

교육 기관: Himanshu G

2017년 12월 30일

great course but it would be better if you ask students to submit their code and give limits and various test cases like an actual programming contest.

교육 기관: aditya s c

2019년 1월 25일

very good teaching of algorithms.however a little help for coding those would be appreciated.(in my case i am dealing with graphs for the first time).

교육 기관: wenqin s

2020년 5월 27일

Overall experience is well, the probability overview was fast, require deep understanding with probability and statistics in discrete model.

교육 기관: Diego F

2022년 5월 16일

El curso se me hizo incomprensible sin utilizar el textbook. Pero una vez empecé a leerlo mientras hacía el curso, se me hizo más sencillo.

교육 기관: Sergey Y

2019년 3월 24일

Content is great. But handwriting is hard to understand clearly for non-native english speakers. I expected good quality of presentations.

교육 기관: VIBIN V

2018년 7월 28일

excellent course

slightly fast paced and optional exercises are challenging . one should solve those as well to get in depth practice.

교육 기관: Saumya S

2020년 4월 2일

Teaching is absolutely perfect. (A grade). But the content in this sub-division of the specialization is very much theoretical.