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.
This course is part of the Mastering Software Development in R Specialization
About this Course
Skills you will gain
- Programming Tool
- Continuous Integration
- R Programming
Syllabus - What you will learn from this course
Getting Started with R Packages
Documentation and Testing
Licensing, Version Control, and Software Design
Continuous Integration and Cross Platform Development
- 5 stars52.05%
- 4 stars23.74%
- 3 stars13.69%
- 2 stars3.65%
- 1 star6.84%
TOP REVIEWS FROM BUILDING R PACKAGES
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).
Fantastic course... Unfortunately, not too many people registered, it's tough to get your assignments graded. The program is the great continuation to the 10 course R data science specialization...
It teaches the up-to-date approaches, in a concise and also systematic way
This is a critical skill and it's barely covered anywhere else. Thanks for making this course!
About the Mastering Software Development in R Specialization
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