# Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Algorithms,

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).

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Rating 4.7★ based on 583 ratings 5 weeks 4 weeks of study, 4-8 hours/week Dec 14 (6 weeks ago) \$79 Stanford University via Coursera Tim Roughgarden On all desktop and mobile devices English Programming Mathematics Computer Science Algorithms Math And Logic

## What people are saying

computer science

This course is must for any Computer Science student This course is about following topics: large integers multiplication, merge sort, quick sort, master method and Karger's min-cut algorithms.

I guess I should go and read the maths for computer science resource.

divide and conquer

Hoppefully, there is a github branch with that already... but better to merge it to here Great learning experience Now I truly understand how to think of algorithm in terms with Recursion applying Divide and Conquer, and how to use Master method to prove an algorithm's complexity.

A very good course for having the notion of algorithms, identify problems which can be solved by divide and conquer approach and analyse their time complexity.

tim roughgarden

Tim Roughgarden explains things in a crystal clear way.

A lot of new thing i have learn from this course Tim Roughgarden does an amazing job at explaining this topic.

professor roughgarden

Thank you professor Roughgarden, and I hope you create another course with advanced algorithms with latest developments.

Professor Roughgarden makes complex algorithm topics easy to understand.

well explained

Concepts are very well explained and the quality of quizzes are top-notch.

Very well explained course content and good quiz and programming assignments.

easy to follow

But still awesome experience and challenge This is not very beginner-friendly course, and what made it worse is that all the videos are out of sync (I don't know why this problem has not been addressed for 5 years), and the instructor's speaking manner is not easy to follow for a foreigner.

The words the professor used are not easy to follow for a non-native English, the way the exercises are designed is not reasonable.

looking forward

Definitely looking forward to the next course in the specialization.

Looking forward to completing his other courses when I got time.

feel like

But instead I was exposed to a lot of new concepts and really feel like I got some good experience from it.

I feel like assignments like this are tedious and discouraging to not only learning but thinking for yourself.

data structures

I really love this course, and it had helped me get started in algorithms and data structures.

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

make sure

The teacher is very good and the assignments and quiz also challenges you and make sure that you have viewed the lectures thoroughly.Thanks :) I love Tim's excitement for algorithms.

fantastic course Excellent but make sure to brush up your math logic and probability skills before taking this course!

mathematical analysis

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.

problem sets

On the other hand the fact that you cannot submit assignments or problem sets without purchasing the course is quite annoying.

On all other courses which I have done without purchasing, you were able to do the full course which includes the problem sets etc.

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