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OT-SC-WS-06 | Visualization in science: principles & critical reflections Registration closed Prof. Dr. Dr. Norman Sieroka, Dr. Antonie Haas © manfredsteger/ Pixabay Part 1 Critical reflections: Visua
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OT-ST-WS-10 | Data base skills Registration closed Prof. Dr. Sebastian Maneth © Tumisu/Pixabay Relational data is ubiquitous and the majority of data is stored in relational database management system
OT-ST-WS-03 | Erste Schritte mit MATLAB Registration closed PD Dr. Christian Fieberg © Pexels/Pixabay Programming language (like Python, R oder MATLAB) skills are a necessary prerequisite for working
OT-ST-WS-07 | Reproducibility in science: How and why? Registration closed Dr. Arjun Chennu The reproducibility crisis in science stems not only from historically poor data availability, but also from
OT-ST-WS-04 | Getting started with Python Registration closed Dr. Nikolay Koldunov © StockSnap/Pixabay Currently python is one of the most popular general purpose programming languages. It gains popul
OT-ST-WS-01 | Getting started with R Registration closed Dr. Christian Fieberg © StockSnap/Pixabay Programming language (like Python, R oder MATLAB) skills are a necessary prerequisite for working wit
OT-ST-WS-06 | Git / GitHub Registration closed Nico Harms © Bessi/Pixabay Git is one of the fundamental tools used in software engineering and collaborative document writing. Paired with platforms lik
OT-ST-WS-05 | How to write a data management plan? Registration closed Prof. Dr. Frank-Oliver Glöckner, Dr. Ivaylo Kostadinov, Jimena Linares, Tanja Weibulat © geralt/Pixabay Research data is constant
OT-SC-WS-04 | Evaluating machine learning and artificial intelligence algorithms Prof. Dr. Werner Brannath, Dr. Max Westphal © manfredsteger/ Pixabay Artificial Intelligence (AI) and Machine Learning
OT-SC-WS-02 | Quantitative analyses for data science Registration closed Prof. Dr. Thorsten Dickhaus © Elchinator/ Pixabay Proficiency in (mathematically grounded) quantitative data analysis is key to
