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Retour à Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Avis et commentaires pour d'étudiants pour Divide and Conquer, Sorting and Searching, and Randomized Algorithms par Université de Stanford

4.8
étoiles
4,256 évaluations
802 avis

À propos du cours

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)....

Meilleurs avis

KS
13 sept. 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.

DT
26 mai 2020

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

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676 - 700 sur 782 Avis pour Divide and Conquer, Sorting and Searching, and Randomized Algorithms

par Ali I C

4 janv. 2020

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.

par Joe

29 avr. 2017

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.

par Gonzalo G E

8 avr. 2018

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.

par Emin E

27 janv. 2018

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.

par Pablo J

28 août 2019

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

par Xiaoliu W

12 juil. 2020

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.

par Ahmad B E

9 mai 2017

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.

par Ivan C

13 nov. 2019

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.

par Madhumala J

27 mars 2019

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

par Dmitriy M

28 avr. 2018

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

par Justin S

29 janv. 2019

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!

par Mayank K

16 janv. 2020

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.

par Himanshu G

30 déc. 2017

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.

par aditya s c

25 janv. 2019

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).

par wenqin s

27 mai 2020

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

par Sergei I

24 mars 2019

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

par VIBIN V

28 juil. 2018

excellent course

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

par Saumya S

2 avr. 2020

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

par Soroush

19 févr. 2020

Course content is satisfyingly rigorous. However, the lack of community support and interaction heavily affects the experience.

par Mohammed S M A

17 sept. 2018

Very nice course, but some parts are not clear because the instructor talks really fast and goes over some parts very quickly.

par Edson A S

9 mai 2020

Great course.

Tim Roughgarden is an incredible teacher.

You'll learn more using Tim's books on the subject, by the way.

par Taylor N

12 juil. 2018

Good explanations, but more theoretical and math-intensive than practical. Not the best way to prepare for interviews.

par Ojas

28 mars 2020

One of the best courses without a doubt!. Although some topics course require more deep / comprehensive discussion

par Youya W

5 sept. 2019

The pace was kind of fast for learners with little base, better to have more reading to facilitate understanding.

par Laxmidhar P

1 juil. 2018

This Course was awesome and it can prove benefit to all the students for designing efficient and fast algorithms.