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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

1,594 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 :)


126 - Understanding and Visualizing Data with Python 的 150 个评论(共 313 个)

创建者 Lorena P G

Jul 13, 2020

It is a very robust course with a lot of details!! Thank you all professors!

创建者 Shashank N B

Jun 08, 2020

Best with the content and lecturing.Have got more knowledge on many aspects.

创建者 Phuong

Aug 05, 2020

This is a great course! The instructor lectured very easily understandable.

创建者 Daniil K

Jul 31, 2020

Very good course. More info about practice, but lack of formuls and theory.

创建者 Wonjun K

Jul 29, 2020

Excellent course to hit the ground running with data science using Python.

创建者 Ritesh J

Dec 03, 2019

Excellent course. Gives you basic understanding on visualization in Python

创建者 Gabriel R G

Feb 17, 2020

I loved it, it´s very useful if you want learn python focused in database

创建者 Yaron K

Jan 26, 2019

A good introduction to visualizing data using the Python seaborn library

创建者 Eduardo A C

Jun 20, 2020

Very practical and consistent with data we need to work in real events.

创建者 Patricia C G

Mar 19, 2019

I loved this course! Thank you for sharing all your knowledge with us!

创建者 Ezequiel P

Oct 06, 2020

Great course. Really gives you a different perspective on the subject

创建者 Beom J P

Sep 28, 2020

This course is best for someone who wants to gain statistics insight.

创建者 Jainil S

Apr 10, 2020

Very good course to kick start career in data science and statistics.

创建者 Olusola T O

Jul 08, 2020

This course will be the one to recommend to a lot of people like me.

创建者 Mark M

Mar 22, 2020

Great course, but I'd prefer fewer videos and more slides/exercises.

创建者 Xun Z

May 17, 2020

This class helps me recall the basics of statistics and programming


Jul 09, 2020

Great course to explore univariate and bivariate data with Python.


Jul 29, 2020

Great! Learn some fundamental statistics knowledge with python.

创建者 Fasasi T

Mar 10, 2019

I love this course, the simplicity and explanation is excellent

创建者 Abhimanyu A

Jun 14, 2020

Very Good course for understanding visualisation and sampling.

创建者 Ernesto J S B

Jun 08, 2020

Great Course to learn Statistics and Python. Great Teachers.

创建者 Mukkamala R

Sep 05, 2020

It was a great experience with some outstanding content.

创建者 Yugesh K

Jun 02, 2020

The best course to start with statistics for a beginner.

创建者 Md I

Apr 19, 2019

This is the best course in this website in entry level

创建者 Varga I K

Mar 20, 2019

It was great setup for statistical analysis in python.