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学生对 密歇根大学 提供的 Understanding and Visualizing Data with Python 的评价和反馈

1,464 个评分
295 条评论


In this course, learners will be introduced to the field of statistics, including where data come from, study design, data management, and exploring and visualizing data. Learners will identify different types of data, and learn how to visualize, analyze, and interpret summaries for both univariate and multivariate data. Learners will also be introduced to the differences between probability and non-probability sampling from larger populations, the idea of how sample estimates vary, and how inferences can be made about larger populations based on probability sampling. At the end of each week, learners will apply the statistical concepts they’ve learned using Python within the course environment. During these lab-based sessions, learners will discover the different uses of Python as a tool, including the Numpy, Pandas, Statsmodels, Matplotlib, and Seaborn libraries. Tutorial videos are provided to walk learners through the creation of visualizations and data management, all within Python. This course utilizes the Jupyter Notebook environment within Coursera....



May 22, 2020

Excellent course materials, especially the videos, with content that is thoughtfully composed and carefully edited. Very good python training, great instructors, and overall great learning experience.


Aug 03, 2020

Great course to learn the basics! The supplementary material in Jupyter notebooks is extremely valuable. Really appreciate the PhD students who took the time to explain even the simplest of codes :)


251 - Understanding and Visualizing Data with Python 的 275 个评论(共 294 个)


Jul 22, 2020

The course is really good.The explanations are in detail but the assignments should be tougher.


May 12, 2019

Coursework is great and so are the teachers , concepts are taught in a easy to understand way.

创建者 Vineet S S

Apr 12, 2020

More examples could have been used to explain concepts in the 4th week of the course. Thanks

创建者 John S W

Sep 30, 2019

Excellent course. Wish I had had more feedback, or someway to interact with an instructor.

创建者 Nicola D L

May 31, 2020

Light-hearted but fairly rigorous. Material is well explained and examples are compelling.

创建者 Partha S

May 13, 2019

It's a wonderful course. Each and every part is well designed and very well explained. i

创建者 vivek n

Apr 15, 2019

Very helpful in understanding sampling stats...using python is like a cherry on top :)

创建者 Mohammad S S

Jul 27, 2020

This course is designed in the best manner you can ever approach to the data science.

创建者 harsh s

Nov 14, 2019

Just a tad slow for my pace, but the understanding and course material are on point.

创建者 Shakshi M M

Aug 17, 2020

Very good course if you are a beginner at learning python and data visualization

创建者 Philippe B d A L

Aug 13, 2020

This course is awesome. If week 4 have more practice, would be excelent!


Apr 20, 2020

Helped me understand some basic concepts of statistics, and insightful.

创建者 Inti L

Apr 03, 2020

Great Introduction Course to statistics concepts and python!

创建者 lokesh k

Jul 28, 2020

Very good starter course for statistics using python.

创建者 Md. M H

Jul 10, 2020

Pretty good to learn, have greatly enjoyed it!

创建者 Felipe B

Jan 14, 2020

Pretty interesting and well paced course.

创建者 Gerard C

Jul 07, 2020

Helpful introduction to the topic

创建者 Mahmoud A H

May 31, 2020

half of week 4 is almost a trash

创建者 Joffre L V

May 26, 2019

Great course, excellent!!!

创建者 Dhruv R D

Aug 23, 2020

Very nice Course

创建者 K K

Feb 24, 2020

excellent course

创建者 Aditi A

Apr 26, 2020

Worth Learning

创建者 Liu M

Jan 14, 2020

great course

创建者 Ata M

Feb 01, 2019

nice effort

创建者 Mikel A

May 14, 2020

In overall the course is good. However, there are some issues that could be improved, as for example:

- Using the NHANES database is come cases is not the most effective as you can spend some times trying to indetify or search for the variable they are asking for. Better instructions or the use of a simpler database could be an alternative.

- Some videos could be improved. There are compilation errors in the Python demostrative videos, in some other cases previoulsy not-explained functions are used (while similar functions already known by the alumn are available) or Python 2 functions are proposed (the course should be oriented to Python 3).

- I found that both parts of the course (stats and programming) are not always perfectly coordinated.

Despite these issues, the course is good and I will go to the next course with them.