Data Science Tools Illustrated Study Guides

Data Science Tools Illustrated Study Guides

These data science tools illustrated guides are broken up into four distinct categories: data retrieval, data manipulation, data visualization, and engineering tips. Both online and PDF versions of these guides are available.


Twin brothers and educators Afshine and Shervine Amidi, creators of past fantastic machine learning and deep learning study resources, are back and at it again, this time with a set of illustrated study guides for an array of data science tools.

This set of illustrated study guides for data science tools was born out of an MIT class that Afshine is currently teaching, though the brothers created the resources in tandem.

What exactly is covered in these guides? They are broken up into four distinct categories, each category containing between one and three individual related guides. The below links redirect to the online versions of these guides; PDF versions are available further below.

 
Data retrieval

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Concepts covered in this guide include: filtering, conditions and data types; types of joins; aggregations, window functions; table manipulation

 
Data manipulation

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Concepts covered in these guides include: filtering, conditions and data types; types of joins; aggregations, window functions; data frame transformations; conversions made easy between R and Python

 
Data visualization

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Concepts covered in these guides include: scatterplots, line plots, histograms; boxplots, maps; customized legend; conversion made easy between R and Python

 
Engineering tips

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Concepts covered in this guide include: version control with Git; working with the terminal with Bash; mastering editors with Vim

 
If you prefer PDF copies of these resources, you can find links to the individual downloads here.

Alternatively, you can access a single “super study guide” which has all of this material available in one document.

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These data science tools illustrated study guides are a great resource for becoming familiar with the concepts covered within. Thanks again to Afshine and Shervine for another thorough resource.

 
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