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Reproducibility of quantitative research is essential for robust research findings. But did you ever wonder if your analysis can be re-run by someone else?

This workshop teaches you the skills to make your code reusable by others.

In this designathon we explore and research the concept of transdisciplinary working in the field of AI.

The course offers a step-by-step guide on how to conduct a meta-analysis, interpret its findings, and effectively communicate the results.

This course focuses on doing research with which researchers not only aim to understand societal issues but also wish to contribute to social change.

This workshop teaches you the skills to be more resilient.

The objective of this course is to support you in designing (brushing up, revising) your research project in such a way that you will achieve your research aim.

This workshop provides an introduction to a number of statistical analyses with SPSS, one of the worldwide most popular statistical software packages.

Academic output is often inaccessible to non-academic audiences. This course aims to tackle these challenges.

In this course the instructor will illustrate the application of R with practical examples. R is widely used open-source software environment for data analysis.