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.
Building R Packages
Building R Packages
This course is part of Mastering Software Development in R Specialization
Instructors: Roger D. Peng, PhD
Sponsored by Barbados NTI
10,937 already enrolled
Gain insight into a topic and learn the fundamentals.
4.1
(223 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 20 hours
Learn at your own pace
97%
Most learners liked this course
Skills you'll gain
- Continuous Integration
- R Programming
- Open Source Technology
- Continuous Delivery
- Rmarkdown
- Configuration Management
- GitHub
- Continuous Deployment
- Software Versioning
- Statistical Machine Learning
- Version Control
- CI/CD
- Software Development Tools
- Knitr
- Statistical Programming
- DevOps
- Git (Version Control System)
- Software Configuration Management
- Software Development
Details to know
Shareable certificate
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Assessments
2 assignments
Taught in English
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This course is part of the Mastering Software Development in R Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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- Develop job-relevant skills with hands-on projects
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There are 4 modules in this course
What's included
1 video16 readings1 assignment
What's included
14 readings1 peer review
What's included
25 readings1 assignment
What's included
13 readings1 peer review
Instructors
Instructor ratings
3.7 (8 ratings)Offered by
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Learner reviews
4.1
223 reviews
- 5 stars
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Showing 3 of 223
MM
5
Reviewed on Nov 15, 2020
This is an excellent course, a really good starting point to learn how to build R packages.
GB
5
Reviewed on Jul 6, 2017
It's one of better course for building packages!!!
MA
5
Reviewed on Jan 15, 2017
Very good course for intermediate/advanced R users. Sad that you are elegible to do assignments only if you pay.
Recommended if you're interested in Data Science
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