This training teaches you how to effectively gather and document requirements in AI-based projects — both for internal processes and collaboration with external partners. The goal is to provide practical foundations and methods to help you fully leverage the potential of artificial intelligence.
The course provides a practical introduction to model-based systems engineering. Using a consistent open-source example from the automotive sector, it demonstrates how model-based abstraction can be used to effectively manage the complexity of developing safety-critical systems.
Until now, software and systems engineering has focused on ensuring the reliability and security of relatively small, centralised and automated systems that operate in predictable environments. However, current and future requirements are increasingly shifting towards ensuring the trustworthiness of larger, dynamically networked, self-learning and constantly evolving, often autonomously acting systems. In the Software & Systems Engineering research focus area, fortiss is expanding the classic methods of model-based software and system development and integrating them with new development methods for data-driven applications.
The AI Engineering research area focuses on researching and developing a new generation of robust, trustworthy AI technologies that can make timely, safe decisions in uncertain and unpredictable environments. Our goal is to increase the trustworthiness and explainability of AI systems and ensure they are resilient to erroneous inputs and targeted attacks. The focus here is on processing large volumes of data as well as gaining knowledge from small amounts of data without jeopardising confidentiality and privacy.
In the IoT Engineering research focus area, fortiss develops flexible, software-based infrastructures that adapt dynamically to changing requirements. We integrate sensor, computer and communication capabilities into heterogeneous systems and penetrate critical infrastructures using software. Our focus is on the creation of resilient, decentralized systems, the transparent management of data and the further development of communication networks. We combine edge and cloud computing to enable efficient, secure and scalable IoT solutions for modern, dynamic environments.
