The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
This course is part of Algorithms Specialization
Instructor: Tim Roughgarden
Sponsored by Coursera Learning Team
79,192 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(1,265 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 14 hours
Learn at your own pace
95%
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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
Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim's MST algorithm.
What's included
16 videos4 readings2 assignments
Kruskal's MST algorithm and applications to clustering; advanced union-find (optional).
What's included
16 videos2 readings2 assignments
Huffman codes; introduction to dynamic programming.
What's included
11 videos1 reading2 assignments
Advanced dynamic programming: the knapsack problem, sequence alignment, and optimal binary search trees.
What's included
10 videos3 readings3 assignments
Instructor
Instructor ratings
4.8 (78 ratings)Offered by
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4.8
1,265 reviews
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Showing 3 of 1265
SC
5
Reviewed on Sep 23, 2017
A more explanatory answer sheet would be helpful. Might need to be secured via limited time login session to avoid leaking on the web.
YA
5
Reviewed on Feb 4, 2021
This course has wonderful lectures coupled with challenging but rewarding homework problems. It was a wonderful learning experience.
SC
5
Reviewed on Dec 31, 2020
Best (not one of the best) course available on web to learn theoretical algorithms. You will love it. Enjoy new journey and perspect to view and analyze algorithms. Loved it damn!
Recommended if you're interested in Computer Science
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