Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part course builds on the principles that you learned in our Principles of Computing course and is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to real-world computational problems.
Algorithmic Thinking (Part 1)
Algorithmic Thinking (Part 1)
This course is part of Fundamentals of Computing Specialization
Instructors: Luay Nakhleh
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4.6
(376 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 12 hours
Learn at your own pace
92%
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Shareable certificate
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Assessments
2 assignments
Taught in English
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This course is part of the Fundamentals of Computing Specialization
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There are 4 modules in this course
What is Algorithmic Thinking?, class structure, graphs, brute-force algorithms
What's included
15 videos2 readings1 assignment
Graph representations, plotting, analysis of citation graphs
What's included
3 readings1 peer review2 app items
Asymptotic analysis, "big O" notation, pseudocode, breadth-first search
What's included
9 videos1 assignment
Connected components, graph resilience, and analysis of computer networks
What's included
3 readings1 peer review1 app item
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Learner reviews
4.6
376 reviews
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Showing 3 of 376
GG
5
Reviewed on Mar 8, 2019
Great course, please offer an oline program to obtain an Rice university grade in science computer.
GJ
4
Reviewed on May 13, 2016
Project is interesting, bu the video lecture is kind of repetitive and does not cover much
RQ
4
Reviewed on May 29, 2016
The content is great. I enjoyed learning about graph theory. The new platform is pretty frustrating, though. The discussion boards are not as vibrant as they were before the paywall.
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