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Bewertung und Feedback des Lernenden für Algorithmic Thinking (Part 1) von Rice University

339 Bewertungen
68 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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26 - 50 von 67 Bewertungen für Algorithmic Thinking (Part 1)

von Andrey S

13. Okt. 2016

Too much bla, bla, bla. Very slowly, very boring.

von Tudor B

4. Apr. 2021

Enjoyed every piece of it. While it assumes you are familiar with programming in Python for which it is recommended to take their "Principles of Computing" both Part 1 and 2 prior, plus knowing some high-school math, it teaches you to develop efficient algorithms that solves particular problems. You will be able to reason about Algorithmic efficiency as well.

von Justin M

18. Feb. 2020

Very challenging course, but I did enjoy the content quite a lot. The programming assignments were well-structured and built upon one another to the point that the final graph resilience project took me an entire weekend to complete, but greatly expanded my understanding of both python data structures and how to represent graphs using them.

von Ze C

27. Feb. 2017

Application assignment is a must-do for students taking this course. The second computer network application is very a rewarding one for me to finish with gains on concepts of graph as well as programming stretch with my hands dirty.

von Jayadev H

22. Aug. 2018

lectures are a bit on the slow side... not straight to the point and a bit repetative..

bfs we have already done in this spezialization.

but homework/project/applications are excellent!

makes up for the rest!

Thank you!

von Tom F

5. Sep. 2020

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

von Prashanth K

23. Okt. 2020

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

von Zou S

16. Okt. 2017

Very impressive and interesting. Graph theory is really elegant representation of the computer network.

von Rachel K

19. Aug. 2017

The project-based course structure works really well for the material. This was a great course!

von Y A

11. Okt. 2017

This is Wonderful and simpler explained course that is detailed with 'learner's requirement'.

von Edwin R

12. Nov. 2017

The course content is well structured and the instructors' explanation is clear and concise!

von Gundala S R

24. Juni 2016

One of the best course offered by coursera, helps you to develop very strong basics if new,.


15. Juni 2020

The explanation of the videos is incredible, it helps you improve, your analytical skills

von emmanouil k

10. Juli 2016

optimization and fragmentation..algos arithmos olokliroma..fractal resilience..

von Jaehwi C

11. Dez. 2017

The best course to study computer science and algorithm for beginner!

von Michael B R

7. Dez. 2017

Another great course in this specialization!

von Albert C G

2. Dez. 2017

Great Class - Truly makes you think

von Isuru

12. Okt. 2016

A course I enjoy very much!

von Jeffrey C

21. Nov. 2019

Very challenging course

von Siwei L

23. Dez. 2017

Very helpful course!!

von Deleted A

16. Juli 2017

Good for it lovers

von Nathaniel B

9. Okt. 2017

Excellent course!

von Guanyu B

24. Okt. 2020

Great course!

von Arthur-Lance

15. Aug. 2017

thanks a lot

von Martin W

19. Feb. 2017

great course