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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

1,580 个评分
315 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 :)


276 - Understanding and Visualizing Data with Python 的 300 个评论(共 313 个)


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 Akshit A

Sep 19, 2020

Assessments too easy. Course material was good though.

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


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 Elvan V

Oct 01, 2020

Keep it up

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.

创建者 Maytat L

Jul 08, 2020

Overall good but still have rooms to improve. I knew so little about statistics and Python. The concept is quite difficult but relatively new unlike other typical statistics courses offer. Practice assignments are very good but difficult. More guidance of Python libraries usage would help. Passing assignments were too easy. Strong foundations of using Python especially in libraries such as matplot, numpy, panda, seaborn would really help to better understand the concepts with a graphical presentation in Python. I would recommend this course for those who are familiar with those Python libraries already. For me, I need to learn more about those and would revisit the content here again to better grasp full understanding.

创建者 Jaime A C V

Apr 08, 2020

The topics that were seen in the course started in a very basic and understandable way but they evolved to much more advanced and difficult topics without a good explanation.Sometimes I felt no connection between theory and practice with Python. The large number of teachers does not allow continuity in learning and creates gaps.

创建者 Hossein P

Nov 01, 2019

This course started well, but unfortunately, I think they should add more extra example and focus on the topics more in-depth, I can say in each quiz I spend around 3 hours to find related topics in the internet and learn them to answer to the questions and I think it should be cover by the course itself.

创建者 kamalakannan

Jul 26, 2020

It's great course to understand the basic concepts of statistics like uni-variate and bi-variate data.But,the assignment which they give week 3 and week 4 is not that much to implement the concepts practically. Overall ,it is a good course.

创建者 asher b

Dec 10, 2019

Good stats course. Needs more Python. Much of the Python is just watching or clicking run. Would appreciated more opportunity to walk through the coding with hints and hidden solutions to gain some proficiency.

创建者 Yaroslav B

Apr 24, 2019

There is incorrect course title for this course as in reality it’s Statistics AND partial illustration of it using Python. There is no consіstent exposition on Python libraries and frameworks.

创建者 Jung W G

Sep 27, 2020

I think the order of lab components should be rearranged. Introduction of core python mechanics should come before the module in which each code is implemented.

创建者 Vikram J

Oct 20, 2020

Very long videos, even the simplest concept is explained in a slower manner. But this is true for me and a lot might benefit from this pace.

创建者 Rakesh D

Jan 20, 2020

Lectures are boring and very long it should be more practical ,but yes I've gain certain statistical insights.