Algorithmic Thinking (Part 1) by Rice University
Experienced computer scientists examine and solve computational issues at a higher degree of abstraction than any programming language. This two-part course expands on the principles acquired in Principles of Computing course and is aimed at teaching students the mathematical concepts and technique of "Algorithmic Thinking," which will enable them to create simpler, more efficient solutions to real-world computational issues.
In part one of this course, students will learn about algorithmic efficiency and how to apply it to a variety of graph theory problems. Students will develop many essential graph algorithms in Python and then utilize these algorithms to analyze two enormous real-world data sets as the course's centerpiece. The major goal of these assignments is to comprehend the relationship between the algorithms and the structure of the data sets that these algorithms are analyzing.
Students should be familiar with building intermediate-size (300+ line) Python programs and have a basic understanding of searching, sorting, and recursion. Students should also have a strong academic foundation, including algebra, precalculus, and a working knowledge of the arithmetic ideas presented in "Principles of Computing."
This course offers:
- Flexible deadlines: Reset deadlines in accordance to your schedule.
- Certificate : Earn a Certificate upon completion
- 100% online
- Beginner Level
- Approx. 12 hours to complete
- Subtitles: Arabic, French, Portuguese (European), Greek, Italian, Vietnamese, Korean, German, Russian, English, Spanish, Telugu
- Course 5 of 7 in the Fundamentals of Computing Specialization
Coursera Rating: 4.6/5
Enroll here: https://www.coursera.org/learn/algorithmic-thinking-1
