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.
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- 5 stars52,05 %
- 4 stars23,74 %
- 3 stars13,69 %
- 2 stars3,65 %
- 1 star6,84 %
Meilleurs avis pour BUILDING R PACKAGES
This is a critical skill and it's barely covered anywhere else. Thanks for making this course!
Very good course for intermediate/advanced R users. Sad that you are elegible to do assignments only if you pay.
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).
Overall, this was a good course to learn the intricacies of building R packages.
À propos du Spécialisation Mastering Software Development in R
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