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Kursteilnehmer-Bewertung und -Feedback für Mathematical Thinking in Computer Science von University of California San Diego

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1,847 Bewertungen
432 Bewertungen

Über den Kurs

Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. We will use these tools to answer typical programming questions like: How can we be certain a solution exists? Am I sure my program computes the optimal answer? Do each of these objects meet the given requirements? In the course, we use a try-this-before-we-explain-everything approach: you will be solving many interactive (and mobile friendly) puzzles that were carefully designed to allow you to invent many of the important ideas and concepts yourself. Prerequisites: 1. We assume only basic math (e.g., we expect you to know what is a square or how to add fractions), common sense and curiosity. 2. Basic programming knowledge is necessary as some quizzes require programming in Python....

Top-Bewertungen

AD
25. März 2019

The teachers are informative and good. They explain the topic in a way that we can easily understand. The slides provide all the information that is needed. The external tools are fun and informative.

AM
27. Feb. 2021

It is a great course! teachers explain everything with care. While providing lectures there are some popup ques that verify whether you understood that lecture or not. Overall, a great experience.

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251 - 275 von 424 Bewertungen für Mathematical Thinking in Computer Science

von ASHTON N

8. Juni 2020

Amazing course

von SYED S

29. Dez. 2020

cool and best

von Zhe Y

21. Juli 2018

learned a lot

von Yuhua Y

9. Okt. 2017

nice course

von Afnan A

15. Aug. 2020

Thank you!

von venus v p

31. Mai 2018

wonderfull

von Madhan C

26. Jan. 2021

excellent

von Raymond B S

22. Dez. 2020

Thank you

von GADAMSETTI V M G

22. Nov. 2020

Excellent

von M L J

22. Okt. 2020

GOOD GOOD

von pavankumar p

9. Sep. 2020

excellent

von Kallinatha H

24. Mai 2020

very good

von N R S

20. Mai 2020

Excellent

von evans

9. Sep. 2019

very good

von Miguel A D A

3. Okt. 2018

Perfect!

von Gaurav R P

1. Okt. 2017

love it.

von 121910316063 g

19. Jan. 2021

good

von 221910311052 S N

19. Dez. 2020

good

von 2K18/EC/038 A R

30. Nov. 2020

Good

von maripalli s

1. Aug. 2020

good

von Ricky I S

17. Aug. 2020

Overall this was a good course. I was also studying the topics from other sources and reading Discrete Mathematics and Its Applications by Rosen and doing all the exercises at the end of each section of Rosen. I felt like the lectures in this course give a very basic overview but do not really get you to the point that you will be ready to apply what you learn to different problem situations. For example, logic was covered in about 20 minutes worth of video but is a 100-page chapter in Rosen, and for one to feel comfortable doing exercises as presented in Rosen or as seen on the homework assignments of many universities, you will need more exposure to the material. This may have been the case because this course is titled Mathematical Thinking in Computer Science and was previously called What Is A Proof? and their intention was not to really teach anything other than that and the other courses in the Specialization will get more into the specifics topics covered in Discrete Mathematics. I still plan on taking the other courses in this specialization as I feel that after reading Rosen and working out the problems in Rosen, its nice hearing some of the material covered again and only serves to reinforce principles. This course has a nice amount of interactive exercises that allow one to practice solving puzzles of sorts. I enjoyed those, although do not think they are sufficient to overcome the lack of practice doing different problems. Note to instructors: More exercises in logic to assess and develop ability in logic would be nice as its a very important part of Discrete Mathematics. If logic is only covered in this class in the specialization and isn't retaught in more depth in the other courses in this specialization, then it is not really being covered properly in this Specialization in Discrete Mathematics.

von Ethan H

15. Juli 2020

Good overall, but week 6 in particular was below my expectations. The students should not be answering questions in order to correct errors in the lecturer's phrasing; you should simply do the sensible thing and re-record the lecture, ensuring accuracy before posting. The final (albeit optional) project of the course is to write a solver for the 15-puzzle. This involved some graph theory self study, since graph theory is out of the scope of this course. A hastily explained intro to graph theory during the final lecture without slides is not sufficient to prepare the students for this task. I would strongly suggest a revision of the entire 6th week.

von Saptarshi M

6. Sep. 2018

This course helps you to put your arguments forward to convince self and other people. There are several techniques to do that. Sometimes providing a single example does the trick while providing counter examples become necessary in other situations. Learners of this course will get new insight about known puzzles. How to find examples is an important part of this course. Alex and Michale are pretty good to put the thoughts that they have. Other lecturers sometimes may confuse pupil. Overall a great start to learn discrete mathematics.

von Christopher P

21. Feb. 2018

Pretty good course, although the topics were sometimes confusing. I think this is to be expected given the nature of the topic, as it's a whole new way of thinking about mathematical problems. I wish the course put some of the techniques used when solving the puzzles into a more explicit or formal context. After some of the puzzles, I was left wondering how to generalize the specific problem-solving technique or insight.

von John A B

4. Okt. 2019

I followed along pretty well but there where a few parts that the instructors just sort of hand waved the developing the formula's needed to solve the theorems. Also the programming questions where always clear about how they wanted the return object represented. This led to some try and error, falling the question to see what little feed back it would give, making a change to the subroutine and then trying again.