This repository covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers.
Specialization : Mastering Software Development in R Specialization
- Course 1 : The R Programming Environment
- Course 2 : Advanced R Programming
- Course 3 : Building R Packages
- Course 4 : Building Data Visualization Tools
- Course 5 : Mastering Software Development in R Capstone
There is a manual Mastering Software Development in R.pdf for these courses.
- Week 1 : Basic R Language
- Week 2 : Data Manipulation
- Week 3 : Text Processing, Regular Expression, & Physical Memory
- Week 4 : Large Datasets
swirl::install_course("The R Programming Environment")
- Week 1 : Welcome to Advanced R Programming
- Week 2 : Functional Programming
- Week 3 : Debugging and Profiling
- Week 4 : Object-Oriented Programming
swirl::install_course("Advanced R Programming")
- Week 1 : Getting Started with R Packages
- Week 2 : Documentation and Testing
- Week 3 : Licensing, Version Control, and Software Design
- Week 4 : Continuous Integration and Cross Platform Development
- Dynamic Documents for R using R Markdown introduce some useful functions and also packages for R users.
- Advanced R designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R's quirks and shows how some parts that seem horrible do have a positive side.
- Efficient R programming teach us how to use R programming efficiently.