Nos formateurs experts

Adam Furmanczuk

he/him

Software Architect & Pragmatic Engineering Coach

Software architect with over 15 years of hands-on development experience across highly regulated industries including banking compliance, border control, healthcare, and robotics middleware. Adam has designed and scaled systems from early MVPs to enterprise platforms, coordinating distributed teams of 120+ developers across the DACH region. He knows exactly when code needs to be elegant and when pragmatism wins to ship on time. He specializes in pragmatic, production-ready architectures using Java, C#, Angular, Flutter, Docker, AWS, and arc42/DDD methodologies. He only teaches what he has personally deployed, debugged, and scaled in production. His approach focuses on real code over theory. Teams learn to identify over-engineering, manage technical debt effectively, and build architectures they will still enjoy working on years down the line. Pragmatic, production-ready, and directly applicable.

Björn Wilmsmann

he/him

AI-based automation, AI-augmented software engineering, Spring, Java, web technologies

Independent IT consultant, trainer, and published author with deep expertise in Java, Spring Boot, and cloud-native architectures. As co-author of "Stratospheric: From Zero to Production with Spring Boot and AWS," Björn has helped thousands of developers navigate the path from local development to production-ready cloud deployments. He specializes in digital transformation, helping businesses automate processes, improve software quality, and make critical data accessible through well-designed APIs. His client work spans enterprise application development, architecture and design reviews, Angular and Spring Boot training, and hands-on coaching of development teams across industries. Björn brings a pragmatic, business-focused approach to technology. Whether advising on architecture decisions, conducting software quality audits, or running customized workshop formats, he focuses on delivering measurable impact and enabling teams to work independently with new technologies.

Katharina Schmidt

she/her

Ingénieure en Machine Learning & Data Scientist | Experte en Computer Vision

Ingénieure en machine learning et data scientist expérimentée, avec une expertise approfondie dans le traitement automatisé d'images et le travail avec des données non structurées. Katharina a participé à de nombreux projets de recherche internationaux et a obtenu son doctorat dans le domaine de la microscopie intelligente. Pendant cette période, elle a dispensé des cours magistraux et des séminaires dans une grande université allemande afin d'aider des étudiants en génie électrique et en mécatronique à développer des compétences essentielles en IA et en deep learning. Outils & Frameworks : PyTorch, TensorFlow, scikit-learn, pandas, PySpark, NumPy, MLflow, MatLab, Snowflake, Amazon Web Services et Databricks

Marcus Nitschke

he/him

IT-Projektconsultant

IT project consultant and Product Owner with a passion for products that deliver real value. Thanks to his many years of experience in the digitalisation of critical processes, he knows exactly how to translate requirements precisely and guide stakeholders confidently through technological transformation projects. With a background in engineering and a deep understanding of complex IT architectures, he acts as a bridge between business, product, and development. As a trainer, Marcus stands out through his ability to combine this hands-on expertise with agile methodologies, enabling teams to develop user-centred and technically sound solutions with real impact.

Pawel Sawicki

he/him

Ingénieur Machine Learning Senior

Ingénieur en Machine Learning et Architecte Logiciel avec plus de 15 ans d'expérience, spécialisé dans le deep learning, le NLP et les systèmes basés sur les LLM. Forte orientation vers la conception et le déploiement de pipelines d'IA de bout en bout, incluant le fine-tuning de modèles (LoRA/PEFT), la génération augmentée par récupération (RAG) et l'inférence haute performance avec des frameworks modernes tels que PyTorch, Hugging Face Transformers et vLLM. Expérience dans la construction de systèmes agentiques utilisant LangChain et LangGraph, ainsi que dans le développement de services backend évolutifs en Python. Combine des principes d'ingénierie logicielle solides avec une expertise pratique en IA centrée sur les données pour livrer des solutions robustes et prêtes pour la production.