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Back to Algorithmic Thinking (Part 1)

Learner Reviews & Feedback for Algorithmic Thinking (Part 1) by Rice University

4.6
stars
383 ratings

About the Course

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. In part 1 of this course, we will study the notion of algorithmic efficiency and consider its application to several problems from graph theory. As the central part of the course, students will implement several important graph algorithms in Python and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to understand interaction between the algorithms and the structure of the data sets being analyzed by these algorithms. Recommended Background - Students should be comfortable writing intermediate size (300+ line) programs in Python and have a basic understanding of searching, sorting, and recursion. Students should also have a solid math background that includes algebra, pre-calculus and a familiarity with the math concepts covered in "Principles of Computing"....

Top reviews

PS

Oct 22, 2020

A great course with wonderful explanations from the tutors. Looking forward to do more courses with this team

TF

Sep 4, 2020

Significantly more difficult than the preceding courses in the specialization, but the projects are fantastic!

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76 - 76 of 76 Reviews for Algorithmic Thinking (Part 1)

By GARSONDIYA A

Jan 31, 2024

bad peer review system