The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis).
Graph Search, Shortest Paths, and Data Structures
Graph Search, Shortest Paths, and Data Structures
This course is part of Algorithms Specialization
Instructor: Tim Roughgarden
Sponsored by BrightStar Care
89,308 already enrolled
Gain insight into a topic and learn the fundamentals.
4.8
(1,983 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 13 hours
Learn at your own pace
93%
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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
Breadth-first and depth-first search; computing strong components; applications.
What's included
9 videos4 readings2 assignments
Dijkstra's shortest-path algorithm.
What's included
4 videos2 readings2 assignments
Heaps; balanced binary search trees.
What's included
9 videos1 reading2 assignments
Hashing; bloom filters.
What's included
9 videos3 readings3 assignments
Instructor
Instructor ratings
4.8 (129 ratings)Offered by
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4.8
1,983 reviews
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Showing 3 of 1983
TG
5
Reviewed on Nov 30, 2019
It was an awesome experience to learn from such a teacher. Now I have a much clear view of the graph algorithms. I have enjoyed this course. Thanks to Stanford for offering this course.
AA
5
Reviewed on Apr 8, 2020
The best algorithms course available. More on the theoretical side which in my opinion is more important, if theory is understood, implementation becomes second nature.
JE
5
Reviewed on Dec 27, 2019
I am very confident in the skills I learned. I have read some books on algorithms but this course makes the application so clear regardless of your programing language.
Recommended if you're interested in Computer Science
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