Call for participation

• A. Janz
• Consulting , Data , RDM , HPC , Data Science , Artificial Intelligence , Machine Learning

Call for participation!

The Data Literacy Center Rhine-Ruhr (DKZ.2R) issues a call for participation in its “rent-an-expert” project! We offer support for ambitious research projects of PhD students and early postdocs dealing with Data Science and Artificial Intelligence, High Performance Computing and Simulation, and Research Data Management. As the DKZ.2R is funded by the German Federal Ministry of Education and Research (BMBF) as well as the EU, this offer is free of charge!

By DKZ.2R: Seminar - Statistical and Machine Learning Methods

Course Description and Goals:

Statistical learning is a field that teaches students how to analyze and interpret data by applying statistical methods and machine learning algorithms to uncover patterns, make predictions, and gain insights from data. The syllabus includes: • Statistical and machine learning methods, including linear and polynomial regression, logistic regression, and linear discriminant analysis. • Model validation techniques such as cross-validation and bootstrap, model selection, and regularization methods (ridge and lasso). • Nonlinear models, splines, and generalized additive models. • Tree-based methods, including random forests and boosting. • Support-vector machines and an introduction to causal inference. • Unsupervised learning methods such as principal components analysis and clustering (k-means and hierarchical). Examination Format: Report and Presentation. Further information, including locations, and Zoom links, can be found on our homepage: https://oek.wiwi.uni-due.de/studium-lehre/lehrveranstaltungen/sommersemester-26/statistical-learning-vorlesung-17350/

Carpentries Workshop - Introduction to Python

• C. Gonzalez
• Training , Workshop , Python

Empowering Researchers with Foundational Computing Skills: Join the Upcoming Carpentries Workshop

In today’s fast-paced research environment, the ability to harness computational tools effectively can make a world of difference. Whether you’re managing data or automating tasks, having the right skills can significantly streamline your work. That’s where The Carpentries come in — a global initiative comprising the Software Carpentry, Data Carpentry, and Library Carpentry communities. These communities are dedicated to equipping researchers with essential computational and data science skills, helping them to work smarter, not harder.