Courses Using R

R is free open source software that has come to dominate the statistical programming environment, along with Python.  It originated as an open-source alternative to the commercial package S-PLUS, which, in turn was derived from S.  Between R and Python, R has a richer set of statistical and machine learning modeling packages and is often preferred for the development and prototyping of models, while Python is often preferred for its data handling and performance capabilities.

Most courses last 4 weeks and consist of readings, supplemental materials, exercises, and a private discussion forum with fellow students and the instructor. Readings and homework are released on a week-by-week basis, and during each week there are no particular times when you must be online. At the end of each week, you submit your homework (you'll get marks and individual feedback in a few days).

Courses in R fall into the following categories:

I. Using R as a statistical package

II. Learning how to program in R - for those new to programming

III. Building R programming skills - for those familiar with R, or experienced with other programming languages or statistical computing environments

IV. Applying R to specific domains or applications

Thanks to Gregory Piatetsky at KDNuggets for his annual software poll: R and Python are the most popular overall tool in the KDNuggets community, and Python usage is growing rapidly.  The continuing widespread use of SAS and IBM-SPSS in the commercial community is not reflected in the preferences of this community.


Top Analytics Tools and Trends

Here are the top tools by share of usage in the KDNuggets community: 

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