Person responsible for module: Dr. Konstantin Hopf

Contents:
The module covers methods of modern decision theory and practice and teaches the most important
concepts of data-driven decision support. The main topics covered include
• the analysis of multi-criteria decision situations,
• decision-making with scenarios (known or unknown probability of occurrence),
• bias and heuristics in decision-making,
• structuring of complex decisions,
• the Analytic Hierarchy Process (AHP),
• portfolio selection and optimization,
• data-driven insights through Business Intelligence and advanced analytics,
• expert systems and decision support systems, as well as
• ethical and legal aspects of data-driven and automated decisions.
The students will apply the learned contents practically on the

Learning outcomes:
Students will be able to
• analyze and model complex decision situations considering several goals, alternatives, and decisionmakers,
• include uncertainties and probabilities in the analysis and modelling,
• include the results of Business Intelligence and Advanced Analytics in decisions,
• develop a simple expert system, and
• describe selected ethical and legal aspects of data-driven decisions.

Organizational details:

• 6 ECTS / 180 h
• prerequisites for the module: none
• Recommended prior knowledge: none
• Frequency: every summer semester
• Mode of Delivery: Lectures and Tutorial - 4,00 SWS
• Language: German/English
• Examination: Written examination / Duration of Examination: 90 minutes