Today’s infrastructures and industries routinely produce abundances of data that can be leveraged to quantify the infrastructure’s resilience. However, such analyses are complicated by the fact that this data is often dynamical (changing over time), heterogeneous (different types of data), interconnected (state of one components depends on the state of many other components) and multirelational (there exist multiple types of dependences). This course has the aim to equip the attendants with the required methodological and formal skills in order to make sense of such data and leverage it for resilience assessment in a self-contained way. The course consists of three units. Unit 1 introduces the basics of probability theory and the theory of random processes. Unit 2 introduces network analysis as a data mining tool. Unit 3 shows an in-depths application example of these concepts in the area of systemic risk in the finance sector. The course requires basic familiarity with the mathematical fields of analysis and linear algebra (knowledge on matrices, differential equations, etc.). The course is based on the lecture “Complex Systems” taught at the Medical University of Vienna by Stefan Thurner, Peter Klimek, and Rudolf Hanel.