# 学生对 斯坦福大学 提供的 Divide and Conquer, Sorting and Searching, and Randomized Algorithms 的评价和反馈

4.8
4,203 个评分
790 条评论

## 课程概述

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)....

## 热门审阅

KS

Sep 14, 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

May 27, 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

## 226 - Divide and Conquer, Sorting and Searching, and Randomized Algorithms 的 250 个评论（共 770 个）

Aug 06, 2019

Best Course for Programmers. But this course needs some programming prerequisites to understand the concepts clearly.

Mar 02, 2018

Good course to get started with algorithms. I am already a programer, and still learn a lot from this course. Thanks!

Aug 16, 2019

Although some concepts were a bit too hard to chew, this is a great start for someone who's new to computer science.

Oct 13, 2017

The course is really good. Helping me to grasp the basic concepts of algorithm and to refresh the algorithms skills.

Sep 25, 2020

excellent content. Learned a lot! Proofs can be a bit dull at times. But that probably simply lies in their nature.

Aug 06, 2020

This was an amazing course and it allowed me to learn complex algorithms and introduced me to algorithmic thinking

Jun 08, 2018

It really helped me understand the concept of algorithms. I confess that I have a new perspective of an algorithm.

Oct 14, 2020

Very intellectually stimulating. The problems were thought-provoking and assessed understanding very effectively.

May 10, 2018

Great teacher. Coming from a science background myself, I like that the math is not watered down in the analysis.

Mar 22, 2020

What an amazing and insightful course. the min algorithm totally blew my mind randomized algo are simply elegant

Dec 10, 2017

Wonderful explanations. The companion book helps a lot to review material and have it always fresh in your mind.

Sep 11, 2019

Awesome course. Learnt a lot about the theory behind a randomized algorithm. Karger's min cut was a revelation.

Apr 30, 2019

He can tend to go off topic and waste time in an effort to be exactly exact, but other than that, great course.

Jun 22, 2018

The material is explained really well and the programming assignments are challenging but ultimately solvable.

Oct 14, 2017

Excellent, great explanations and good pace. Exercises quite challenging for a newbie but you'll learn a ton.

Aug 04, 2017

Slides are concise. By going through all the slides, I'm already able to grab most of the information needed.

Jul 02, 2020

Some of the homeworks were difficult, but implementing the algorithms is the best way to really learn them.

Jun 08, 2017

A little hard to understand, but if you have done your preparation readings, it would be extremely helpful!

Jun 03, 2017

Great Course! Everyone should take this cousere in order to become a skilled programmer.

Not for begginers.

May 16, 2017

Amazing course. Tim is a very charismatic lecturer and it is always a pleasure to get back to his lectures.

Jan 09, 2017

Tim Roughgarden teaches with wit and depth. Speaking with idiomatic verve, he injects life into Algorithms!

Jun 29, 2020

Thank you Tom. This is a great course. I got a real vision of the algorithms and started to understand it.

Apr 05, 2018

Can you do better in those technical interviews?

Yes! if you take this course.