R FOR DATA SCIENCE

This course is aligned with the Infocomm Technology Skills Framework for Data Analyst and Data Scientist and will use R, a widely used statistical package. The course aims to quickly bring up to speed a programmer or business analyst who already knows how to programme in other language or have done advanced Excel macros to begin using R as a data science tool. The course will define data science and explore the first two things a data scientist must do – cleaning and visualising data. You will learn and use R’s dplyr, ggplot and ggvis packages for these tasks. It will then cover the Data Science Workflow – training models and testing them through the application of machine learning models to various industry-relevant data science problems. The tool used will be the Caret package. At the end of the course, you should have a working knowledge of how to solve data science problems with R and the following: - Use R for basic data munging to aggregate, clean and process data from local files and access databases and REST APIs - Create visualization with R/ggplot/ggvis - Create basic to intermediate analytics models with the R Caret package - Learn 12 common analytics models and how to programme and apply them in R