Chevron Left
Вернуться к Processing Data with Python

Отзывы учащихся о курсе Processing Data with Python от партнера Coursera Project Network

4.4
звезд
Оценки: 191
Рецензии: 27

О курсе

Processing data is used in virtually every field these days. It is used for analyzing web traffic to determine personal preferences, gathering scientific data for biological analysis, analyzing weather patterns, business practices, and on. Data can take on many different forms and come from many different sources. Python is an open-source (free) programming language that is used in web programming, data science, artificial intelligence, and many scientific applications. It has libraries that can be used to parse and quickly analyze the data in whatever form it comes in, whether it be in XML, CSV, or JSON format. Data cleaning is an important aspect of processing data, particularly in the field of data science. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Лучшие рецензии

PK
25 сент. 2020 г.

Instructor Explains very well in the programming part and as well as project guidance thank you Coursera for offering such a wonderful Lectures and project tutorials Thank you once again

AK
17 авг. 2020 г.

Great project to begin understanding data processing in python

Фильтр по:

1–25 из 27 отзывов о курсе Processing Data with Python

автор: PAMARTHI K

26 сент. 2020 г.

Instructor Explains very well in the programming part and as well as project guidance thank you Coursera for offering such a wonderful Lectures and project tutorials Thank you once again

автор: Ashwin K

18 авг. 2020 г.

Great project to begin understanding data processing in python

автор: BORRIS L S

23 июня 2020 г.

Really good if u know beginning python programmer

автор: Md. F I

15 июня 2020 г.

Worth a try. Good for getting an overview

автор: Daniela R L

8 нояб. 2020 г.

quick and easy, very basic

автор: Gangone R

5 июля 2020 г.

very useful course

автор: Jesus M Z F

18 июня 2020 г.

Excelente curso

автор: Syam K K S

11 окт. 2020 г.

Recommended

автор: Doss D

23 июня 2020 г.

Thank you

автор: MOHAMMED B

16 июня 2020 г.

thank you

автор: Kamlesh C

24 июня 2020 г.

thanks

автор: Md. M

21 июня 2020 г.

Great!

автор: p s

23 июня 2020 г.

Good

автор: VIVEK K

12 июня 2020 г.

nice

автор: René C

22 авг. 2021 г.

Interesting 'quick learning' course which puts you through a number of regular challenges that any Python developer will face in his career. Thanks to this short course, those challenges have been presented in a structured manner, which saves time and allows me to continue with other projects without having to dwell on the lower level details of 'how to manipulate Python' for large data sets.

автор: Fajle S H

25 июня 2020 г.

Thank you Coursera to give me this type of courses. Already I love python programming language. But after seeing this type of courses,I was very excited that how processing any data by this language. Thank You COURSERA......

автор: Aditya A S

21 июня 2020 г.

Yes, the project/course with respect to its length was helpful.

Check out more learnable amazing skills regarding programming: https://www.youtube.com/channel/UCdNOTa62J6j1109NQfxHqdg/playlists

автор: Somesh M

18 июня 2020 г.

its nice course good opportunity to learn a small thing to create a grate objective

автор: Sahil P G

3 июля 2020 г.

Good choice if anyone wants to get started with Pandas and data processing.

автор: Vedhavalli L

17 июня 2020 г.

superb

автор: MD. A E

27 июня 2020 г.

good

автор: Lokesh P

6 авг. 2020 г.

good

автор: Adnan

12 июля 2020 г.

The explanation is very less in every part of this project. The instructor just keeps introducing stuff like I am proficient in Panda and came to take a review. Very less explanation on every part, but I have learned a new thing, Panda and its basic's basic!

автор: Steven F

23 июля 2020 г.

The web platform used is difficult to navigate.

автор: Mohammad D A

13 июня 2020 г.

It could have been more interesting.