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.
Getting Started with R Packages
Documentation and Testing
Licensing, Version Control, and Software Design
Continuous Integration and Cross Platform Development
Part of the Mastering Software Development in R specialization. Probably one of the worst online courses available to online learners anywhere. The material is poorly structured, poorly presented and utterly confusing. But don't worry you should get up to speed chewing your tongue after a few weeks and by the end you may be relieved to die from a brain haemorrhage.
Kanyika. Rodgers Funtukeni
Kanyika. Rodgers Funtukeni is taking this course right now, spending 3 hours a week on it and found the course difficulty to be medium.
Buildind r pakages was a combination of greater learning Of achive to ma standed point of view. That i have earned knoledge