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Вернуться к Python Data Analysis

Отзывы учащихся о курсе Python Data Analysis от партнера Университет Райса

4.7
звезд
Оценки: 803
Рецензии: 134

О курсе

This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs. These concepts and skills will help you to further extend your Python programming knowledge and allow you to process more complex data. By the end of the course, you will be comfortable working with tabular data in Python. This will extend your Python programming expertise, enabling you to write a wider range of scripts using Python. This course uses Python 3. While most Python programs continue to use Python 2, Python 3 is the future of the Python programming language. This course uses basic desktop Python development environments, allowing you to run Python programs directly on your computer....

Лучшие рецензии

AS
15 мая 2020 г.

One of the best course in this specialization. It was really interesting work with some real world data which could really enhance the problem solving skills.

NL
6 июля 2021 г.

Great programming practice, especially the project for week4. I am more comfortable with lambda now. I am much more helpful to my son in Python classes.

Фильтр по:

126–135 из 135 отзывов о курсе Python Data Analysis

автор: Andrew M

1 февр. 2018 г.

I feel like this course needs a lot of polish. The practice assignments in particular are riddled with horrible grammatical errors that make it hard to figure out what is being asked of you, especially when the author seems to be trying to be overly concise in their explanations. There's also too much reliance of documentation research. It felt like every assignment just told me to read page after page of documentation and figure out what parts were relevant on my own. Documentation research is obviously an important skill, but telling a student to learn an entirely new skill like color mapping based purely on documentation, and not telling them what parts of the documentation to focus on verges on cruel. I've never felt as frustrated with an assignment as I did with several in this course. The way the assignments were designed also made them very hard to test. The disconnect between the practice assignments and the graded assignments also caused a lot of issues with regards to flow. It feels like two courses were smashed together, one of which was fairly well built, the other of which was very much not.

My comments mostly pertain to the practice assignments. I thought the graded assignments were pretty good.

автор: Nicoletta H

3 мар. 2020 г.

I brought prior basic knowledge of python which I think helped a lot completing this course. It is definitely challenging, but one learns a lot if you are willing to do your own research. The whole specialization works with videos, personally I prefer getting a bit of text, too. But this is personal preference. Only the final project - I don't know what they were thinking. It is overly complicated and the descriptions could have been a lot clearer. I'm not sure the course adequately prepares for this. Do your research on the discussion forums, otherwise you might have a hard time. Because of how the project is conceptualized, I feel like I can't really add it to my portfolio, which is really a pity.

автор: Youssef F

4 мая 2020 г.

The course is really fruitful. It covers everything I needed. What didn't work well for me was the last assignment.

A project with baseball theme isn't really a good idea, at least for me !

But i really enjoyed the course ! Thank you for this opportunity and for your efforts.

автор: Matt O

15 февр. 2021 г.

A found this to be a very basic course. Not much in the way of analysis. Mostly just contorting lists / dicts / tuples. Would have preferred getting int Pandas / Numpy and other tools for actually analysing the data. A bit misleading, to be honest.

автор: Mads J K H

28 мар. 2018 г.

Could use a bit more explanation on some parts since visualization of e.g. dictionaries can be a bit tedious.

Otherwise good.

автор: vikram B

16 окт. 2020 г.

Best Course on CSV handling ,we also have move fexibility with file handling with panda looking for course on that

автор: Oleh M

22 июня 2019 г.

A very sharp combination of the basics on lectures and algorithms in practice.

автор: Madhubalini V

22 сент. 2020 г.

its rushing,concepts are not fully explained to a beginner

автор: Weerachai Y

28 июня 2020 г.

thanks

автор: Chen A

21 июля 2020 г.

作业链接打不开