Introduction to R
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.
Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Take your R skills up a notch by learning to write efficient, reusable functions.
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Learn the essentials of parsing, manipulating and computing with dates and times in R.
Learn how to pull character strings apart, put them back together and use the stringr package.
Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.
Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.
Learn to easily summarize and manipulate lists using the purrr package.
Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.
Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.
Continue learning with purrr to create robust, clean, and easy to maintain iterative code.
Learn defensive programming in R to make your code more robust.
Use C++ to dramatically boost the performance of your R code.
Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.