Developed as statistics software, R offers the perfect basis for working with data. Thanks to a very active developer community, R keeps growing and gaining useful functions. Both Python and R are the de facto cornerstones of modern data science.
This course focuses on data preparation, analysis and visualization with the so-called tidyverse package. This collection of useful functions makes working with large amounts of data easier and enables impressive visualizations. Most modern scientific publications use the tidyverse package to stand out with its professional graphics.
It covers typical approaches in the data science field, and participants learn how to plan and carry out a data science project and communicate it clearly to a broad audience. It also places particular emphasis on reproducible, well-documented work.
Topics
- Fundamentals of data management
- Data preparation
- Data types and their implications
- Fundamentals of high-dimensional data analysis (e.g. distances and dimensionality reduction strategies)
- Data analysis and visualizations with tidyverse
- Interpreting data and communicating it clearly
Requirement: Some initial basic experience with R, for example from our introductory R course.