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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Divide and Conquer, Sorting and Searching, and Randomized Algorithms
This course is part of Algorithms Specialization
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Instructor: Tim Roughgarden
Sponsored by PKO BP
247,762 already enrolled
(5,270 reviews)
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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
Instructor
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Reviewed on Jan 26, 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.
Reviewed on Mar 15, 2017
Very good course in algorithms. I bought the book to help me understand but the lectures make it way easier and thus much more fun to understand the analysis. Looking forward to complete the spec
Reviewed on Jun 15, 2018
Challenging and eye opening to algorithm design paradigms. As a code writer for data analysis in a scientific field, this course really motivated me to delve deeper in this rich field.
Recommended if you're interested in Computer Science
Coursera Instructor Network
Indian School of Business
Duke University
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