Training & Activities
Symposium ML4QT | Machine Learning to Advance Quantum Technologies
In-person event | Monday 7 - Tuesday 8 July 2025 | experimenta Heilbronn
The symposium Machine Learning to Advance Quantum Technologies (ML4QT) is a forum for researchers and developers passionate about the intersection of machine learning and quantum technologies. Whether you are already active in this exciting field or just beginning to explore it, ML4QT offers the ideal platform to discover opportunities and synergies that will drive the future of quantum technology development.
Quantum Brunch
Webinar Series | 28 March - 11 July 2025 | 10.00 -10.30 am
The "Quantum Brunch" webinar series, hosted by the Fraunhofer IPA Quantum Computing Group, provides a low-threshold, business-oriented introduction to various aspects of quantum computing and quantum technologies. Through short keynote presentations, participants gain foundational knowledge, insights into current research questions, and an overview of potential applications.
QuantumBW Colloquium
Hybrid Event | 20 March – 13 November 2025 | 10.00 – 11.00 am
The QuantumBW Colloquium is powered by QuantumBW to promote scientific exchange in the fields of quantum computing and quantum sensing. It aims to showcase the latest developments in these areas and advance the concept of co-developing quantum solutions.
Introduction to Quantum Machine Learning (English) | Certificate Course
Certified Data Scientist with a specialization in Quantum Machine Learning
Hybrid-Training | 5 May/ 27 October 2025 | Duration: overall 5 Units + Examination Day
This certificate course provides a hands-on introduction to the fundamentals and applications of Quantum Computing and Machine Learning. Participants will learn to understand and apply quantum algorithms and methods such as the Quantum Support Vector Machine. The course is designed for professionals in data science, technology companies, and research institutions.
AutoQML-Framework
Open-Source-Software | Automated Quantum Machine Learning
As part of the collaborative project AutoQML, the Fraunhofer Institutes IAO and IPA, together with seven industry partners, have developed an open-source application of the same name. AutoQML connects quantum computing with machine learning, enabling the use of quantum machine learning algorithms without requiring deep technical expertise.
sQUlearn- Software Library
Python-Library | Quantum Machine Learning (QML)
sQUlearn is an intuitive Python library for quantum machine learning, built to integrate seamlessly with tools like scikit-learn. Its layered architecture supports both experts and beginners, making it easy to explore and apply quantum-enhanced machine learning.
Quantum Lab
Guided Lab Tour | On request, Tuesdays 2 pm - 4 pm | Group Size max. 12 persons
In 1919, Max Planck received the Nobel Prize for his role in developing quantum theory. Over a century later, the Quantum Hardware Lab invites you to explore key quantum phenomena—uncertainty, superposition, and entanglement—through hands-on experiments. Learn the basics of quantum algorithms and discover the potential and challenges of quantum computing. And for a playful twist: brew your own hot drink with the QoffeeMaker, powered by quantum circuits.