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Learner Reviews & Feedback for Understanding and Visualizing Data with Python by University of Michigan

4.7
stars
2,589 ratings

About the Course

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....

Top reviews

AT

May 21, 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.

VV

Aug 2, 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 :)

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501 - 525 of 551 Reviews for Understanding and Visualizing Data with Python

By Jo L

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Apr 20, 2020

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

By Gabriel M

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Jan 15, 2021

Could have used more python assignments or unfilled labs in week 4.

By Inti L

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Apr 3, 2020

Great Introduction Course to statistics concepts and python!

By Devina D

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Jul 10, 2021

It was good overall. A bit fast-paced, but it was good.

By Akshit A

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Sep 19, 2020

Assessments too easy. Course material was good though.

By lokesh k

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Jul 28, 2020

Very good starter course for statistics using python.

By Nero

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Aug 5, 2022

Good introduction course to statistic for beginner

By shebl m

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Dec 12, 2022

very good course content and very good learners

By Md. M H

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Jul 10, 2020

Pretty good to learn, have greatly enjoyed it!

By Joy C

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Feb 14, 2022

A good foundation for Data Science program.

By Felipe B

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Jan 14, 2020

Pretty interesting and well paced course.

By Gerard C

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Jul 7, 2020

Helpful introduction to the topic

By Mahmoud H

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May 31, 2020

half of week 4 is almost a trash

By Angelo M

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Apr 25, 2021

I don't like the last week.

By Joffre L V

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May 25, 2019

Great course, excellent!!!

By Teerthangkar B

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Jul 26, 2021

Very good and insightful

By DHRUV D

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Aug 23, 2020

Very nice Course

By k k

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Feb 24, 2020

excellent course

By aditi a

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Apr 26, 2020

Worth Learning

By Liu M

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Jan 13, 2020

great course

By Ata M

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Feb 1, 2019

nice effort

By Elvan V

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Sep 30, 2020

Keep it up

By 黄存昕

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Jun 2, 2021

not bad

By Mikel A

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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.

By maytat l

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Jul 8, 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.