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Kursteilnehmer-Bewertung und -Feedback für Algorithmic Thinking (Part 1) von Rice University

321 Bewertungen
65 Bewertungen

Über den Kurs

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"....


28. Sep. 2018

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.

16. Sep. 2019

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.

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51 - 64 von 64 Bewertungen für Algorithmic Thinking (Part 1)

von Ganapathi N K

11. Nov. 2017



7. Mai 2020


von Eul S S

23. Aug. 2019


von Cameron B

2. Mai 2016

I found the material of this course to be very enlightening, it's not too difficult if you have the appropriate background. However, it will take a decent amount of time to fully complete. As part of the specialization, all of the skills I've learned were consolidated and put to an interesting use with this class.

von Karun

23. Sep. 2016

The applications were too time consuming. Please consider adding a tool that makes graphing easier. The course itself was very good and engaging and without us knowing it, would teach core fundamentals of computing through the coding exercises.

von Alonso F B R

15. Juni 2020

This course is very good, it teaches you to think and analyze problems, problems and programs are difficult to solve, much prior knowledge is required.

von 이선재

11. Dez. 2020

So difficult to beginner.... It requires some knowledge of python(dictionary, list, and some grammer..)

von Garlic J

13. Mai 2016

Project is interesting, bu the video lecture is kind of repetitive and does not cover much

von Arnob B

21. Sep. 2017

Last assignment was a bit weird but great course otherwise!

von Deepak V

19. Juni 2019

It was a good learning experience

von Wenxuan L

26. Jan. 2020


von Marcello F

10. Sep. 2017

Great course !

von Wynand

10. Jan. 2018

Not quite the same level of energy presents in IIPP and Computing Principles. Also did not like the peer review projects, too messy.

von Qi D

18. Feb. 2017

coursea does not allow me to quit the class. Also, I cannot do the homework or watch video at my own pace.