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

4.7
stars
1,970 ratings
405 reviews

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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276 - 300 of 403 Reviews for Understanding and Visualizing Data with Python

By Kondapalli S V

Feb 20, 2020

wonderfull

By Andria

Nov 2, 2019

Very nice.

By Beatriz J F

Oct 27, 2019

Excellent!

By Yiyi Z

Dec 13, 2020

wonderful

By madhurima c

Aug 28, 2020

very good

By Yurgenis R

Jun 16, 2020

very good

By Satrio T S

Oct 3, 2019

Excellent

By DR. S

Nov 23, 2020

AMAZING!

By Nedal

May 25, 2020

v

e

r

y

g

o

o

d

By Gabriel A A C

Feb 5, 2020

Excelent

By Israel F

Jun 25, 2020

Amazing

By 周晓

Apr 7, 2020

Thanks!

By KAYDAN P R

Jun 30, 2020

awssem

By Frank S Y R

Jan 17, 2019

Nice!

By Hugo S A

May 24, 2021

fun!

By Durga S

Apr 16, 2021

Good

By chang l

Aug 31, 2020

good

By GUNDA S K G

Mar 4, 2020

good

By ATHIPATLA S N

Feb 25, 2020

nice

By BODIREDDI S A

Feb 23, 2020

nice

By PUPPALA B A

Feb 21, 2020

GOOD

By PEDASINGU T K

Feb 24, 2020

gud

By Debasis D

May 12, 2021

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By Jerrold

Oct 7, 2020

There are two main fields of study in this course which forms the foundation for the specialization: statistical theory, and programming with python data analysis packages. I learned so much about statistics and visualization that would have taken months to learn in university, I gained a lot of experience and knowledge from this course. I have a decent background in Jupyter notebook from university yet I still learned many new things and got an excellent chance to practice programming in the python packages. The course offered excellent optional practices and gave us several extremely insightful and educational analysis reports done in JN that were related to the module of the week for us to download.

I recommend you have a datacamp subscription to have access to some extra notes regarding programming in the packages particularly Pandas to get the most out of this course by attempting all the optional programming practices.

By Luis D R T

Oct 26, 2019

I loved several things, first that gives you an overview, useful, clear and fun of several basic statistical concepts such as measures of central tendency, different forms of graphic representation, and one of the most important at least for me (already that neither in school nor I would have ever thought about) the types of sampling that exist, because in school there is usually something called simple random sampling and we develop statistical techniques for it, almost completely ignoring the other types of sampling that are really common in real life and that when we face them we don't panic, I know that this is an easy level and I appreciate that in some way, but I would have expected a more difficult course that would have made the concepts really stay in me because I would be thinking about them continuously and how to apply them to the tasks that are presented week by week