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Opiniones y comentarios de aprendices correspondientes a Mathematical Thinking in Computer Science por parte de Universidad de California en San Diego

4.4
estrellas
1,848 calificaciones
433 reseña

Acerca del Curso

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....

Principales reseñas

AD
25 de mar. de 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 de feb. de 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 de 426 revisiones para Mathematical Thinking in Computer Science

por Adolfo S R B

31 de dic. de 2020

Muy buen curso

por MOHAMED G A E

11 de jul. de 2020

thanks so much

por Snehal P

1 de jul. de 2020

Just Excellent

por ASHTON N

8 de jun. de 2020

Amazing course

por SYED S

29 de dic. de 2020

cool and best

por Zhe Y

21 de jul. de 2018

learned a lot

por Yuhua Y

9 de oct. de 2017

nice course

por Afnan A

15 de ago. de 2020

Thank you!

por venus v p

31 de may. de 2018

wonderfull

por Madhan C

26 de ene. de 2021

excellent

por Raymond B S

22 de dic. de 2020

Thank you

por GADAMSETTI V M G

22 de nov. de 2020

Excellent

por M L J

22 de oct. de 2020

GOOD GOOD

por pavankumar p

9 de sep. de 2020

excellent

por Kallinatha H

24 de may. de 2020

very good

por N R S

20 de may. de 2020

Excellent

por evans

9 de sep. de 2019

very good

por Miguel A D A

3 de oct. de 2018

Perfect!

por Gaurav R P

1 de oct. de 2017

love it.

por 121910316063 g

19 de ene. de 2021

good

por 221910311052 S N

19 de dic. de 2020

good

por 2K18/EC/038 A R

30 de nov. de 2020

Good

por maripalli s

1 de ago. de 2020

good

por Ricky I S

17 de ago. de 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.

por Ethan H

15 de jul. de 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.