[Translate to English:] Master Digital Economy

Digital Network Analytics

Digital Network Analytics I

This course introduces students to the (data) analysis of digital networked systems. Aside from the theoretical background, students will use software tools to apply their knowledge in the analysis of different types of (real-world) networks. After the course, students:

  •  can answer questions such as "Who is important in a network and why?", "How robust is a network against failures or targeted attacks?"

  • understand the definition and the purpose of different network measures;

  • will be able to apply an analysis tool and interpret different measures that the tool provides;

Digital Network Analytics II

This course is about the applied analysis of digital networks, using state-of-the-art software tooling in the programming languages R and Python as well as working on problem sets on real-world data on digital networks. Completing the course enables students:

  • to represent and to persist data on digital networks using adequate data structures;

  • to apply graph-based modelling and analysis techniques on digital network data;

  • to visualise digital networks for reporting purposes;

  • to evaluate and select alternative development techniques to implement programs for digital network analysis;

  • to describe and to evaluate different architectural options for a network-analysis tool chain;

  • to gather first experiences using state-of-the-art software such as NetworkX or igraph;