Our Expert Trainers

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

Machine Learning Engineer & Data Scientist | Expert in Computer Vision

Experienced machine learning engineer and data scientist with extensive expertise in automated image processing and working with unstructured data. Katharina has been involved in numerous international research projects and earned her Ph.D. in the field of smart microscopy. During this time, she taught lectures and seminars at a major German university to help electrical engineering and mechatronics students develop key AI and deep learning skills. Tools & Frameworks: PyTorch, TensorFlow, scikit-learn, pandas, PySpark, NumPy, MLflow, MatLab, Snowflake, Amazon Web Services, and 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

Senior Machine Learning Engineer

Machine Learning Engineer and Software Architect with 15+ years of experience, specializing in deep learning, NLP, and LLM-based systems. Strong focus on designing and deploying end-to-end AI pipelines, including model fine-tuning (LoRA/PEFT), retrieval-augmented generation (RAG), and high-performance inference with modern frameworks such as PyTorch, Hugging Face Transformers, and vLLM. Experienced in building agentic systems using LangChain and LangGraph, as well as developing scalable backend services in Python. Combines solid software engineering principles with hands-on expertise in data-centric AI to deliver robust, production-ready solutions.