R Packages for AI and Machine Learning
March 22, 2024
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This course is part of Mastering Software Development in R Specialization
Instructors: Roger D. Peng, PhD
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Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community-based standards and provides a good user experience. This course covers the primary means by which R software is organized and distributed to others. We cover R package development, writing good documentation and vignettes, writing robust software, cross-platform development, continuous integration tools, and distributing packages via CRAN and GitHub. Learners will produce R packages that satisfy the criteria for submission to CRAN.
1 video16 readings1 assignment
14 readings1 peer review
25 readings1 assignment
13 readings1 peer review
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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Reviewed on Jun 10, 2022
Useful programming exercises to guide learning the basic elements of R packages. Also glad that I got my assignments graded within a week following submission (thought it would take much longer).
Reviewed on Nov 15, 2020
This is an excellent course, a really good starting point to learn how to build R packages.
Reviewed on Mar 12, 2022
The course delivered the basic goals of creating a package for the first time in R!
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