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Wed Apr 1 2026 - Thu Apr 2 Past

Wed - Thu 1 Apr 2026 - 2 Apr 2026Past

Introduction to Machine Learning with Python and Scikit-Learn

Workshop Aachen (RWTH Aachen University)

Workshop Python Machine Learning Carpentries By DKZ.2R

Registration Closed

As part of our “Trainings” work package, the DKZ.2R creates, curates and presents a variety of free trainings, seminars and courses. Our next offering will be a one and a half day carpentries-style workshop on basic machine learning using python and scikit-learn, to be presented at RWTH Aachen University on 1st and 2nd of April, 2026. The workshop will cover the following topics:

What is Machine Learning / Why bother?
Supervised Methods (Regression / Classification)
Ensemble Methods
Unsupervised Methods (Clustering / Dimensionality Reduction)
Neural Networks
Ethics and Implications of Machine Learning

Workshop material is available online and will be presented by instructors who will walk you through the steps and are available for questions throughout the event. The official registration is already closed, for last-minute registrations please contact us via info@dkz2r.de.

All workshop material will also be made available online on GitHub.

A basic familiarity with Python is expected, including writing for loops, conditional statements, using functions, and importing libraries.

Title: Introduction to Machine Learning with Python and Scikit-Learn
When: Wednesday, April 1st (9am-5pm) & Thursday, April 2nd (9am-3pm)
Where: RWTH Aachen University, Germany (Kopernikusstraße 6, 52074 Aachen, Seminarraum 003)
Format: This workshop in In-Person and no remote or online attendance options are currently planned.

Tags:

How To: Open Science

A. Mielke
Data , RDM , Open Science

Tired of Recreating someone else’s work? - How Open Science can accelerate research and overcome reinvention

Have you ever found papers on algorithms but their implementation is missing? Found an interesting analysis but there is no way to check the results, as you don’t have access to the data they were derived from? Ever thought you had a great idea for a project, just to find out a year later that you are not the only research group following that specific idea? Not having access to other people’s code, data, metrics or even their plans for research projects often leads to unnecessary delays and scientific redundancies. There is an easy solution to overcome (almost) all of these issues. It’s called Open Science! What is Open Science? The UNESCO defines Open Science as a construct of “movements and practices aiming to make multilingual scientific knowledge openly available, accessible and reusable for everyone, to increase scientific collaborations and sharing of information for the benefits of science and society, and to open the processes of scientific knowledge creation, evaluation and communication to societal actors […]”. To ensure that everyone has access to scientific knowledge and infrastructure, Open Science focuses on four main concepts.

Data Challenge - Metadata

Are you ready to put your data skills to the test?

Whether you’re a solo researcher, student, or part of a research group — this is your chance to dive into the world of metadata, file naming, and smart data structuring.

Join us for the DKZ.2R Metadata & Data Structuring Challenge

When? November 7th, 10:00 – 16:00

Where? Seminargebäude University of Cologne

What’s it about?

We’ll kick off the day with a compact, hands-on lecture on best practices in data organization and metadata. Then, it’s your turn to shine: Choose between your own project data or a dataset provided by us. Apply what you’ve learned and enter the Challenge.

The Carpentries Workshop: Introduction to Git

The DKZ.2R presents, as a part of our “Trainings” work package, a Carpentries Workshop on the 2nd of February with an “Introduction to Git”. This is an official Carpentries Workshop and will be hosted on-site at the Humboldt-Universität zu Berlin.

Workshop material is available online and will be presented by official Carpentries instructors, who will guide you through the concepts with the help of hands-on exercises and personalized support. The course is designed for beginners and is open to participants from all domains. No prior knowledge is required. If you are interested in taking part in the workshop, you can sign up here.