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Divide and Conquer, Sorting and Searching, and Randomized Algorithms (Coursera)

Divide and Conquer, Sorting and Searching, and Randomized Algorithms (Coursera)

Key Facts

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Provider
School
Language
Level
Coursera
Stanford University
English
Intermediate

By enrolling in this online course you will spend approx. 17 hours to learn key concept of Computer Science Algorithms and Data Structures.

Course Overview

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).

Course Syllabus

Week 1

Introduction; “big-oh” notation and asymptotic analysis.

Week 2

Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.

Week 3

The QuickSort algorithm and its analysis; probability review.

Week 4

Linear-time selection; graphs, cuts, and the contraction algorithm.

Meet your Instructors

Tim Roughgarden

Tim Roughgarden is a Professor of Computer Science and (by courtesy) Management Science and Engineering at Stanford University. He received a BS in Applied Mathematics from Stanford in 1997, and a PhD in Computer Science from Cornell in 2002. His research interests include the many connections between computer science and economics, as well as the design, analysis, applications, and limitations of algorithms. For his research, he has been awarded the ACM Grace Murray Hopper Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), the Kalai Prize in Computer Science and Game Theory, the Shapley Lecturership of the Game Theory Society, the Social Choice and Welfare Prize, INFORM’s Optimization Prize for Young Researchers, the Mathematical Programming Society’s Tucker Prize, the EATCS-SIGACT Gödel Prize, and a Guggenheim Fellowship.

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