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

4,800 calificaciones
935 reseña

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:

876 - 900 de 919 revisiones para Divide and Conquer, Sorting and Searching, and Randomized Algorithms

por Utsav S

4 de jun. de 2020

excellent ,what i most need was asymptotic analysis

por Anish K

30 de ago. de 2017

Very fun, interactive and downright helpful course.

por Yasir M

9 de jun. de 2020

Should be more precise in code. It's too vague

por Dragonphy W

13 de oct. de 2018

It's good enough but lack of thorough analysis

por Yash K

14 de may. de 2017

Requires a bit of Math background for proofs!

por Simon R

13 de feb. de 2020

Interesting and well explained. Well done.

por Deepika G

26 de abr. de 2019

Loved the content and detailed lectures.

por Toader A

6 de dic. de 2020

Mentor help is almost non-existent.

por Dipankar M

10 de may. de 2020

Very nice course with good faculty.

por de P S

8 de ago. de 2020

interesting and challenging course

por Suhui L

24 de abr. de 2022

The profofessor speaaks too fast

por Artem S

23 de abr. de 2017

Sometimes too much mathematics.

por Sanul R

19 de sep. de 2018


por Michael L

19 de dic. de 2018

This course is excellent...

por Shouvik G

3 de ago. de 2018

good.but, he is so fast!

por Tejas P

14 de jun. de 2018

well explained sir..!!!

por Tabrez M

28 de abr. de 2020

good explanation

por 张之晗(ZhiHan Z

27 de ago. de 2017

so challenging

por Shuvro C D

10 de sep. de 2021

good course

por Thành N K

29 de jun. de 2019

very hard

por Prachi M

25 de jun. de 2017


por E.Naveen K

30 de nov. de 2016


por Parag K D

3 de abr. de 2022


por Bianca D

26 de ene. de 2019

Took me way more than 7 hours/week to go through course materials and complete the problem sets and programming assignments. Closer to 10. In general the estimates for how much time each assignment takes is way off (often claiming on the order of minutes, when the reality is for most students (myself included) it is likely on the order of hours).

That said, the programming assignments were challenging and fun (especially trying to do them in JavaScript), and I feel much more comfortable with recursion and Big-Oh.

The forums for the current session are not very active, but there are a lot of old posts from past offerings of the course, and I found that most of the time others had similar questions to me.

The textbook was helpful, but it pretty much has the same content as the lectures with maybe some extra practice and challenge problems. Unfortunately not all solutions to those problems are available, which can be very frustrating (I noticed at least one practice problem with no solution was used on the final exam, so that’s probably why...).

This course is a little more academic than practical in my opinion as a software engineer, but you have to start somewhere.

por Peter C

12 de feb. de 2017

I was glad to get exposure to famous algorithms through this class, but I don't feel like I really developed an intuition for reasoning about their runtime. The class was challenging, but mostly for the wrong reasons. I spent more time and energy pouring over the answers to tricky quizzes and having to implement algorithms exactly as described in the lecture notes rather than really truly learning. It also took me much longer than the 4-8 hours per week advertised to complete each week.