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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
4,198 évaluations
788 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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651 - 675 sur 769 Avis pour Divide and Conquer, Sorting and Searching, and Randomized Algorithms

par Wan H L

1 oct. 2017

The instructor offers me a very clear explanation on different algorithm designs. The assignments are also thought-provoking and is able to stimulate your brain.

One thing for improvement is the sufficiency of algorithm exercise. It seems the algorithm exercise the course offers is not enough for those who would like to pursue higher challenge in algorithm puzzles.

par Daniel Z

18 févr. 2019

Good introductory course: allows to relatively quickly go through the topic without getting stuck in too much detail; hands on assignments are nice and useful. The slides I feel could be further improved to (i) aid rapid understanding, (ii) be more helpful in problem solving and (iii) have a few more maps back to the bigger picture.

par Rishi B

6 juin 2018

This was a good course, but it is not for people who want to get work done using algorithms. It is pretty math heavy and requires ample amount of dedication and understanding. Some high standard videos like the ones on Graph Theory was not very well explained, I had to see some youtube videos to get a nice understanding about them.

par Chris S

7 mars 2018

I thought the course was well instructed, Tim is a good professor and doesn't give up too many of the answers. I found the probability section needing more review as I didn't come into the course with a statistics background, and I felt that hurt my full comprehension of the material. Other than that, awesome course.

par Weiming H

23 mai 2018

I really like this course and think that the course is very helpful for me as a non-cs major student to learn more about algorithms.

However, I found it hard to find answers to the quiz and the questions. I tried in the forum but in vain. Might be an improvement of the Coursera system and organization?

par Aniruddha S

6 juil. 2020

Excellent course for students to study why and how the popular algorithms work. The course was very much focused on the math behind the algorithms and I felt it could have been better if the course focussed more on real time applications using the algorithms and their implementations with pseudocode.

par Sandesh K A

16 nov. 2018

Perfect start for a NOOB, all algorithms are explained in a detailed way. Only draw back i felt which can be addressed in further version is to include few programmatic assignments, so that developers can relate how the algorithm is translated from mathematical equation to running code.

par John Z

13 nov. 2017

Sincerely speaking, the lecture is too coarse. It will be more help, if there are more details in lecture. But not only in videos. It is quite waste of time by watching videos one by one. However, by finish this course, I have regained basic algorithm knowledge learned in college.

par Krishna R

23 mars 2018

I took this course to understand more the approach of problem solving and less the mathematical analysis. To understand why the things the way they are , Its sufficient to understand conceptual analysis, rather than mathematical analysis , at least for me.

par Kelvin

28 oct. 2017

The course is awesome and explained in details of every topic. However, watching the videos alone is not enough and in my opinion, read the book that the course recommended or look on the internet for relevant reference to support your learning.

par Sean S

22 juil. 2017

A little too much math than what was anticipated, I would have preferred more of why did the CS choose a divide and conquer approach than proofs. The professor talks faster than I can take notes, it's great that we can stop and rewind.

par Norman W

24 juin 2018

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.

par Pranav H K

17 avr. 2020

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.

par Duy K N

23 août 2018

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

par Rishabh P

31 mars 2020

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...

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