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).
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
Divide and Conquer, Sorting and Searching, and Randomized Algorithms
This course is part of Algorithms Specialization
Instructor: Tim Roughgarden
Access provided by New York State Department of Labor
252,375 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(5,301 reviews)
Intermediate level
Some related experience required
Flexible schedule
2 weeks at 10 hours a week
Learn at your own pace
94%
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Assessments
9 assignments
Taught in English
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This course is part of the Algorithms Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Introduction; "big-oh" notation and asymptotic analysis.
What's included
13 videos3 readings2 assignments
Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms.
What's included
11 videos2 readings2 assignments
The QuickSort algorithm and its analysis; probability review.
What's included
9 videos1 reading2 assignments
Linear-time selection; graphs, cuts, and the contraction algorithm.
What's included
11 videos3 readings3 assignments
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Showing 3 of 5301
SN
5
Reviewed on Mar 26, 2020
I'm happy with this course because is a little challenging, not like other coursers where there are trivial answers and tests. I feel now much more confident with my fundamentals. Thank you Tim!
EE
4
Reviewed on Jan 27, 2018
It would be great if lectures and slides would be with better design and to make and record new slides and lectures. Because these lectures seems too old. Everything else is great.
KS
5
Reviewed on 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.
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