Background

Programming language (like Python, R oder MATLAB) skills are a necessary prerequisite for working with data and applying advanced data science methods.

Learning contents

• R Basics
• Importing and Exporting Data
• Programming Basics
• Datatypes
• Scripts
• Functions
• Basic Plotting Tools

Learning objectives

Learn how to use R to apply data science methods and turn data into insight.

Prior knowledge

none

Technical requirements

• Own laptop

• Connection to Wifi via eduroam or equivalent access (see: https://www.uni-bremen.de/en/zfn/wifi/overview-wifi)

• Access to R or Rstudio
  • Please make sure, you have a functional current version of R or R-Studio before the workshop
  • Participants with access to the Uni Bremen ZfN Services can use R and RStudio via JupyterHub (https://jupyter.uni-bremen.de/).
  • For installation to your own computer download R via https://cran.rstudio.com/ or R-Studio via https://posit.co/download/rstudio-desktop/. Installations will be guided in the workshop.
• If you do not have any programming environment (e.g. Python, R, Rstudio, etc.) installed on your computer, you can use web-based options: For example, participants with access to the Uni Bremen ZfN Services can use the Uni Bremen JupyterHub. Alternatively, participants can use the NFDI JupyterHub.

The Lecturers

Dr. Gerrit Liedtke Dr. Gerrit Liedtke is a Postdoc at the University of Bremen, Faculty of Business Studies and Economics.	Tobias Neumaier Tobias Neumaier is PhD Candidate and Research Assistant at the University of Bremen, Faculty of Business Studies and Economics.

Find out more about the Data Train lectures on our website.

This event is organized by