Today, most complex systems have an underlying network structure. Examples of such networked systems include social networks, power grids, financial/economic networks, transportation systems, or computer networks. This course introduces students to the (data) analysis of complex networked systems. In particular, the Digital Network Analytics (DNA) elective teaches methods and tools to understand and answer questions such as:

• What does the structure of a network tell us?
• Who/what is important in a network, and why?
• How do epidemics, information, or changes spread?
• How robust is a network against attacks?
• How much cargo, information, or energy can be shipped from A to B?

Aside from the theoretical background, students will learn how to use software tools in order to apply their knowledge to the analysis of different types of real-world networks (e.g. social networks, transportation networks, computer networks, financial networks, or power grids) .