Veronika Batzdorfer veronika.batzdorfer@kit.edu
The open source software package R is free of charge and offers standard data analysis procedures as well as a comprehensive repertoire of highly specialized processes and procedures, even for complex applications. After providing an introduction to the basic concepts and functionalities of R, we will go through a prototypical data analysis workflow in the course: import, wrangling, exploration, (basic) analysis, reporting.
By the end of the course participants should be:
- Comfortable with using
Rand RStudio - Able to import, wrangle, and explore their data with
R - Able to conduct basic visualizations and analyses of their data with
R - Able to generate reproducible research reports using
R Markdown - Able to run LLMs locally in
R Studioand evaluate model inference
| Day | Time | Topic |
|---|---|---|
| Friday | 12:00 - 13:00 | Onboarding & Getting Started with R |
| Friday | 13:00 - 13:15 | Break |
| Friday | 13:15 - 14:00 | Data Types & Loading |
| Friday | 14:00 - 15:00 | Lunch Break |
| Friday | 15:00 - 16:00 | Data Wrangling |
| Friday | 16:00 - 16:15 | Break |
| Friday | 16:15 - 17:00 | Data Workflows & Github |
| Day | Time | Topic |
|---|---|---|
| Saturday | 12:00 - 13:00 | Data Wrangling 2.0 |
| Saturday | 13:00 - 13:15 | Break |
| Saturday | 13:15 - 14:00 | Exploratory Analyses |
| Saturday | 14:00 - 15:00 | Lunch Break |
| Saturday | 15:00 - 16:00 | Data Visualization |
| Saturday | 16:00 - 16:15 | Break |
| Saturday | 16:15 - 17:00 | Relational Data |
| Day | Time | Topic |
|---|---|---|
| Monday | 12:00 - 13:30 | Recap & Confirmatory Analyses |
| Monday | 13:30 - 14:30 | Break |
| Monday | 14:30 - 15:00 | Reproducible Reporting with R Markdown |
| Monday | 15:00 - 15:15 | Break |
| Monday | 15:15 - 16:00 | Hands-on R Markdown |
| Day | Time | Topic |
|---|---|---|
| Tuesday | 12:00 - 13:30 | Excursion Shiny APP |
| Tuesday | 13:30 - 14:30 | Lunch Break |
| Tuesday | 14:00 - 14:20 | Excursion Applications in R (LLMs) |
| Tuesday | 14:20 - 14:35 | Break |
| Tuesday | 14:35 - 16:00 | Group data challenge |
| Day | Time | Topic |
|---|---|---|
| Wednesday | 12:00 - 13:00 | Group data challenge |
| Wednesday | 13:00 - 13:15 | Break |
| Wednesday | 13:15 - 14:00 | Group data challenge |
| Wednesday | 14:00 - 15:00 | Lunch Break |
| Wednesday | 15:00 - 16:00 | Group presentations and Wrap-up |