Вернуться к Алгоритмическое мышление (Часть 1)

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Оценки: 345
Рецензии: 69

## О курсе

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"....

## Лучшие рецензии

OT

28 сент. 2018 г.

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.

MR

16 сент. 2019 г.

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 из 68 отзывов о курсе Алгоритмическое мышление (Часть 1)

автор: Andrey S

13 окт. 2016 г.

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

автор: Tudor B

4 апр. 2021 г.

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.

автор: Justin M

18 февр. 2020 г.

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.

автор: Ze C

27 февр. 2017 г.

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.

22 авг. 2018 г.

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!

автор: Tom F

5 сент. 2020 г.

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

автор: Prashanth K

23 окт. 2020 г.

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

автор: Zou S

16 окт. 2017 г.

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

автор: Rachel K

19 авг. 2017 г.

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

автор: Y A

11 окт. 2017 г.

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

автор: Edwin R

12 нояб. 2017 г.

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

автор: Gundala S R

24 июня 2016 г.

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

автор: TOVAR E P S

15 июня 2020 г.

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

автор: emmanouil k

10 июля 2016 г.

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

автор: Jaehwi C

11 дек. 2017 г.

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

автор: Michael B R

7 дек. 2017 г.

Another great course in this specialization!

автор: B. U R

26 июня 2022 г.

A must do course for learning Algorithm

автор: Albert C G

2 дек. 2017 г.

Great Class - Truly makes you think

автор: Isuru

12 окт. 2016 г.

A course I enjoy very much!

автор: Jeffrey C

21 нояб. 2019 г.

Very challenging course

автор: Siwei L

23 дек. 2017 г.

автор: Deleted A

16 июля 2017 г.

Good for it lovers

автор: Nathaniel B

9 окт. 2017 г.

Excellent course!

автор: Guanyu B

24 окт. 2020 г.

Great course!

автор: Arthur-Lance

15 авг. 2017 г.

thanks a lot