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.
About this Course
Rice University is consistently ranked among the top 20 universities in the U.S. and the top 100 in the world. Rice has highly respected schools of Architecture, Business, Continuing Studies, Engineering, Humanities, Music, Natural Sciences and Social Sciences and is home to the Baker Institute for Public Policy.
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TOP REVIEWS FROM ALGORITHMIC THINKING (PART 1)
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.
very educational. I've learnt not only about graph theory but also how to use matplotlib and timeit libraries. The assignments were quite challengeable but rewarding.
The class is very useful, I already see the improvement in the codes that I write. And the assignments are very well-designed and truly helpful.
This is where computer science truly starts, without the excessive preliminary math that usually scares most people away. Great course!
About the Fundamentals of Computing Specialization
This Specialization covers much of the material that first-year Computer Science students take at Rice University. Students learn sophisticated programming skills in Python from the ground up and apply these skills in building more than 20 fun projects. The Specialization concludes with a Capstone exam that allows the students to demonstrate the range of knowledge that they have acquired in the Specialization.
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