AI Act Engineering: From Requirements to Code, 24.11.26

Description: With this course, participants will recognise that many AI Act requirements can be implemented today using existing open-source tools, and understand that established engineering practices naturally support these requirements. They will gain practical knowledge of how compliance components can be integrated into engineering workflows and develop an awareness of the remaining gaps in AI standards and engineering practices. Learning objectives: • You will learn to explain how established engineering practices already support key AI Act requirements. • You will identify relevant points in development workflows where AI Act requirements should be considered. • You will learn how to distinguish between key technical and organisational requirements of the AI Act, with a focus on high-risk AI systems. Target audience: Individuals from small and medium-sized enterprises (SMEs), start-ups and public institutions, in particular technical roles that implement legal requirements, product and project managers responsible for compliance, and anyone responsible for the quality, conformity and safety of AI. Prerequisites: Basic knowledge of machine learning and software development is recommended, but not required. Trainers: Akhil Deo, Senior AI Regulatory Expert, appliedAI Institute for Europe, and Kristof Schröder, Principal Research Engineer, appliedAI Institute for Europe. Many thanks to the community partners of the Bavarian AI Innovation Accelerator for their support in communicating and disseminating the project offerings: BIHK - Bayerischer Industrie- und Handelskammertag e.V., vbw – Vereinigung der Bayerischen Wirtschaft e. V., Bayern Innovativ GmbH, UnternehmerTUM GmbH, Munich Innovation Ecosystem GmbH, fortiss GmbH, German Mittelstand e.V., BAIOSPHERE. This training is offered as part of the Bavarian AI Act Accelerator. The project is funded by the Bavarian State Ministry of Digital Affairs. Details: https://innovationsbeschleuniger.bayern/ --- (DE) Develop step by step an understanding of which engineering practices and tools are suitable for compliance with the AI Act.