Introduction to R programming

by Andre Gohr (MPI-CBG, Scientific Computing Facility)

Monday 14 Sept 2026, 09:30 → 16:30 Europe/Berlin

SR Top Floor (CSBD)

R is a comprehensive environment for scientific computing, data exploration/analysis, and high-quality visualizations. As a free, open-source platform, R serves as an essential everyday tool across diverse academic disciplines — ranging from computer science and biology to the social sciences. It enables researchers to manipulate data, execute statistical computations, and efficiently package their novel analysis tools for peer distribution.

The Scientific Computing Facility invites you to this internal practical course designed to guide beginners through their first steps in R. The course focuses on the fundamentals of programming in R through interactive live-coding; advanced topics such as statistics or package development are not covered.

Objectives:

1. Familiarize yourself with the basics of working with R, including system documentation navigation, package management, and script execution.
2. Execute basic data exploration, covering tabular data ingestion, fundamental data wrangling, manipulation, and storage.
3. Apply the basics of R programming, including variable assignment, data structures, formal logic, and program flow control.
4. Generate standard data visualizations using the built-in base R plotting engine.

 

Level: Beginner

Format: Interactive live-coding; Students repeat the coding examples on their laptops.

Eligibility & Capacity: Restricted to CBG members. Limited to 15 participants.

Prerequisites:

1. Unix Shell Proficiency: Familiarity with file system navigation and command-line software execution.
2. Text Editor Competency: Basic operational knowledge of a simple text editor (e.g., Nano, Vim, Gedit, TextEdit, but not Word or similar.)
3. Hardware & Software: A personal laptop with an installation of R.
4. Prior Experience: General programming experience is helpful but not essential.

 

This workshop is adapted from the official Software Carpentry course Introduction to R and RStudio.