Chevron Left
Volver a Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Opiniones y comentarios de aprendices correspondientes a Divide and Conquer, Sorting and Searching, and Randomized Algorithms por parte de Universidad de Stanford

4,866 calificaciones

Acerca del Curso

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)....

Principales reseñas


13 de sep. de 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.


26 de may. de 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

Filtrar por:

851 - 875 de 928 revisiones para Divide and Conquer, Sorting and Searching, and Randomized Algorithms

por S A

22 de dic. de 2017

Please do not teach graphs before teaching data structures it becomes very tough for students.

por Sahil A

8 de dic. de 2021

Amazing course live deep knowledge about divide conquer algorithms like merge and Quick sort

por Irene J

11 de abr. de 2020

It is a little bit hard for people who only have Python background, but still pretty good.


28 de jun. de 2019

The talking speed of instructor is too fast. Is there a way to slow down via the control?

por Andres M H C

9 de ene. de 2021

Very nice course. The professor speak really fast but the subtitles are really helpful


5 de may. de 2020

instructor speed of telling the concept is very fast so kindly please take care of it.

por Shubham r

24 de ago. de 2019

It was a great course and I loved joining this. Clearing my many theoretical concepts.

por Rui Z

12 de ene. de 2019

Very good course! Clear explanations and proofs to help you understand the algorithms.

por Priyanshu J

4 de abr. de 2020

I would appreciate if implementation of algorithms is also included with this course.

por Rohan K

12 de sep. de 2020

The instructor was really really fast. Grasping the concepts was a little difficult.

por Joey

1 de jul. de 2020

Awesome course, I found it very helpful in preparation for my developer interviews.

por Nikhil S

21 de dic. de 2019

In the very end, it was fun coding the min-cut algorithm and overall I enjoyed this

por Tianyi Z

16 de jul. de 2018

Quicksort could be better. The comparison counting is not a good assignment I feel.

por Lucas P

1 de ene. de 2019

The classes are very good but I hope they can improve the programming assignments.

por Osmar P

10 de feb. de 2021

Extreme well-structured course, but it's really hard to understand the whiteboard

por Dieter V

16 de nov. de 2020

Very well explained. Good selection of programming assignments and problem sets.

por Sukhesh B

14 de nov. de 2016

Great course to improve your skills on Algorithms, Space and Time complexities

por Sriram R

13 de nov. de 2016

Needs hands-on experience with high-school probability to help crack the exams

por Aman S

3 de abr. de 2020

The instructor wasn't very good at teaching, but the course is designed well.

por Ashish U

25 de jul. de 2019

really helpful course on building concepts on data structures and algorithms

por Aditya K

29 de jun. de 2018

Tough one, but if you take time to understand ... it is deep and fun as well

por Yusuf K

20 de ene. de 2018

Excellent set of tutorials. Good questions that require critical thinking.

por Keith M

17 de nov. de 2020

Good course but make sure your up to speed on probability theory first.

por Patel P N

4 de mar. de 2022

One of the besst course available on the internet this Stanford course

por adham E

3 de jun. de 2020

I thin it can be more easier as its first course in the specialization