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Mastering Complexity to Navigate a Complex World
To understand the complex processes that shape our world and to interpret the vast amounts of data available today, a solid foundation of scientific methods is essential. This website serves as a gateway to courses that teach the fundamental tools and concepts for modeling and quantitatively analyzing complex systems. These courses enable students to apply this knowledge within their own fields of study or in interdisciplinary contexts.
InterKI
The InterKI program offers a university-wide curriculum on Machine Learning (ML) and Artificial Intelligence (AI), including foundational modules, advanced modules focusing on applications in various scientific disciplines, and specialized modules on deeper methodological aspects. Additional extension modules provide space for critical reflection on AI in the context of sustainability and ethics, and they also explore the transfer of AI methods into industry.
Navigating Complexity
Understanding the dynamics of complex systems requires more than just knowledge of their individual components. It is crucial to grasp the interactions and emergent phenomena that arise from the interplay between these parts. Such systems are found throughout the natural and social sciences as well as in engineering. Examples include the climate system, interacting species in ecosystems, the dynamics of economic systems, or the electricity grid, to name just a few.
Methodical Sprints
To keep pace with the rapid development of quantitative methods, the Center has established the format of Methodical Sprints. These intensive block courses focus on specific methods and are designed to convey them in a clear and practical way, enabling participants to apply these approaches independently in their own research fields. In doing so, the Center bridges a crucial gap between methodological innovation and academic teaching.