Algorithm Fundamentals: Sort, Search & Randomization
Master fundamental algorithm design techniques including divide-and-conquer, sorting, and randomized algorithms.
Master fundamental algorithm design techniques including divide-and-conquer, sorting, and randomized algorithms.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Algorithms Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.8
(5,224 ratings)
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Instructors:
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Analyze algorithms using asymptotic notation
Implement divide-and-conquer algorithms
Understand randomized algorithm design
Master sorting and searching techniques
Apply graph algorithms and cut problems
Skills you'll gain
This course includes:
10.6 Hours PreRecorded video
9 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course explores fundamental algorithm design paradigms and analysis techniques. Students learn asymptotic analysis, divide-and-conquer strategies, and randomized algorithms. The curriculum covers essential topics including QuickSort, mergesort, Karatsuba multiplication, and graph algorithms. Through programming assignments and mathematical analysis, learners master both theoretical foundations and practical implementations.
Week 1
Module 1 · 3 Hours to complete
Week 2
Module 2 · 4 Hours to complete
Week 3
Module 3 · 3 Hours to complete
Week 4
Module 4 · 4 Hours to complete
Fee Structure
Instructor
A Pioneering Computer Scientist and Game Theory Expert
Tim Roughgarden has established himself as a leading figure in theoretical computer science, particularly at the intersection of algorithms and economics. Born July 20, 1975, he earned his Ph.D. from Cornell University in 2002 under Éva Tardos's supervision, followed by a postdoc at UC Berkeley. He served as a professor in Stanford University's Computer Science department from 2004 to 2018 before joining Columbia University. His research focuses on algorithm design, game theory, and their applications to networks, auctions, and blockchains. His contributions have earned him numerous prestigious honors, including the Grace Murray Hopper Award, the Presidential Early Career Award for Scientists and Engineers, the Gödel Prize, and a Guggenheim Fellowship. As an educator, he has developed widely-used online courses in algorithms through Coursera and authored several influential textbooks including "Algorithms Illuminated" and "Twenty Lectures on Algorithmic Game Theory." Currently serving as a Professor at Columbia University and Head of Research at a16z crypto, he continues to advance the field through his work on the boundary of computer science and economics.
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4.8 course rating
5,224 ratings
Frequently asked questions
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