Lecture series Data Worlds

Why the lecture series is something for you!

The interdisciplinary lecture series Data Worlds teaches students of all subjects the basics of digital and data skills as well as familiarity with data-driven methods. In order to understand digitalisation and datafication, technical-practical knowledge and critical reflection are closely linked and examined from different perspectives.

In the winter semester, the focus is on technical and practical knowledge of information technology systems, simple machine learning algorithms and neural networks. In the summer semester, the social effects of datafication and digitalisation are discussed.

After attending both courses, students will have an overview of current social developments and the technical and practical basics of data-driven methods and will have basic knowledge and familiarity in the field of digital and data literacy (DDL).

The lectures are accompanied ‘hands-on’ by exercises with Jupyter notebooks and R. All courses can be attended without prior knowledge.

Important figures

Data Worlds 1 (winter semester)

In the winter semester, the Data Worlds 1 lecture series examines the basics of statistics, data analysis and machine learning from a technical perspective. The interdisciplinary team is made up of lecturers from computer science and the social sciences. Students learn the following content:

How the information technology data ecosystems that largely shape our everyday lives work

The technical and social interaction of these systems in the collection, storage and use of data

Simple statistical and visualisation methods for the explorative analysis of data

Basic algorithms of supervised and unsupervised machine learning (classification, regression, clustering)

Elementary introduction to neural networks and their applications in image and text processing (Large Language Models)

Recording of the lecture in winter semester 2024/25 (German):

Data Worlds 2 (summer semester)

In the summer semester, the Data Worlds 2 lecture series examines social, political and economic contexts from different perspectives as a result of increasing datafication and digitalisation. The interdisciplinary team is made up of lecturers from different faculties. Students learn the following content:

Overview of the current status of data utilisation and application in various areas of society such as politics, science, education and business

Critical examination of these data applications and their social and ethical challenges such as digital divide, bias and discrimination

Impact of increasing digitalisation and datafication on the political public sphere and journalistic work

Various issues of digital humanities and their development in the context of datafication and artificial intelligence

Possibilities and limits of legal (data protection) and technical (IT security) regulation of data use and their consequences

Accompanying exercises

In both semesters, the lectures are accompanied by practical exercises. In the exercises, methods from the lecture are applied ‘hands-on’ with Jupyter notebooks and R.

Students learn the basics of data analysis with the tidyverse and go through the typical steps of a data-driven research project.

Programming is carried out in the STEM faculty's web-based, interactive coding and development environment JupyterLab.

-> Click here for the JupyterLab

The exercises are rounded off by several literature sessions in which critical reflection on the social consequences of datafication and AI takes place and topics from the lecture are addressed.