R programming has become a useful language in the field of data science. It has allowed practitioners to apply statistical frameworks towards a vast array of data models. But where does one start to learn the principles in the language, and also develop models that are useful?

This workshop will go through the basic usage of R programming including: * Installing R programming * The basic programming protocols in R, including packages and libraries * The basics of RStudio (the IDE used for R) and Visual Studio * R Markdown * How data is accesssed (API, libraries, data files) * Data sources and ideas for managing data types for models * Overview of basic models, from regression to sentiment analysis * A review of Shiny - framework for developing an app * Data visualization with ggplot and other data visualization options will be reviewed