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Understanding and Visualizing Data with Python, Université du Michigan

4.5
40 notes
13 avis

À propos de ce cours

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....

Meilleurs avis

par JS

Jan 24, 2019

I strongly recommend this course to those who want to begin python programming applied to statistics. It launches a very sound foundation for statistical inference theory.

par JS

Feb 06, 2019

Really enjoyed the different (yet all wonderful) teaching styles of the large instructor team!

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13 avis

par Jorge Alfonso

Feb 10, 2019

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par Moid Hassan

Feb 09, 2019

A good introduction on Statistics.

par Jin Shi

Feb 06, 2019

Really enjoyed the different (yet all wonderful) teaching styles of the large instructor team!

par Ata Mustafa

Feb 01, 2019

nice effort

par tuncay dogan

Jan 31, 2019

this course is well below my expectations. there are none real life examples or detailed visualizations, except a few simple plots. There is no step by step coding lectures. There are some youtube videos which are much better than this. Dont waste your time if your goal is to learn python, other than getting some certification.

par Yaron Klein

Jan 26, 2019

A good introduction to visualizing data using the Python seaborn library

par Jadson Paulino Alves da Silva

Jan 24, 2019

I strongly recommend this course to those who want to begin python programming applied to statistics. It launches a very sound foundation for statistical inference theory.

par Frank Salvador Ygnacio Rosas

Jan 17, 2019

Nice!

par Iver Band

Jan 13, 2019

Good introduction to basic statistical methods with an emphasis on working with surveys, and a good introduction to basic statistical techniques with core Python, numpy, matplotlib, seaborn and statsmodels. Instructors and presentations are excellent, very clear. I would give it five stars if it were more interactive, i.e. with more in-video quizzes, and practice quizzes between videos. Also, I wish I had take this course before I did the Applied Data Science with Python specialization, also on Coursera, but, alas, it wasn't available then.

par Kristoffer Hess

Jan 10, 2019

This course still has spelling mistakes in its quizzes, which in a programming focused course are big, and the instructors don't seem interested in fixing them. The result is you have to guess through their mistakes if code is suppose to not work in a quiz because of the error or the error is not supposed to be there in the first place and the code is valid.