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PT25649
Training Summary
A comprehensive exploration for programmers of the features and functionality of the R statistical programming language held over three days. There is an optional half-day programming basic for R that precedes the course for those taking the course that many not have a programming background. As well, an optional half-day statistics refresher course is available.
The course introduces students to the R ecosystem which includes the R programming languages, the various R libraries, the programming language itself and the associated tools like R Studio and R markdown.
Prerequisites
A basic programming knowledge in a high level language is assumed as well as a basic understanding of statistics. Optional half-day primers in both of these areas can be run before the class to ensure that students have the required prerequisites before class begins.
Duration
3 Days/Lecture & Lab
Audience
The course is designed for both programmers and data analysts.
Course Topics
- R Ecosystem Overview
- R Programming Basics
- Data Operations and TidyVerse
- Data Analysis and Visualization
- Functional Programming in R
- Data Cleaning and Transformation with R
- Building Statistical Models with R
- Presenting Reports
- High Performance R Tuning
- Big Data R (optional)
- Machine Learning with R (optional)