About This Course

The course covers multi-criteria decision analysis methods, including AHP, TOPSIS, and ELECTRE, as well as expert systems, knowledge representation, business intelligence, data visualization, and group decision support. Particular attention is given to decision-making under uncertainty using probabilistic models, fuzzy logic, and Bayesian networks.

Upon completion of the course, students will be able to formulate decision problems, select appropriate analytical methods, evaluate alternatives against criteria and constraints, and justify recommendations. They will also be able to design decision support systems and critically assess their outputs, considering data quality, model assumptions, and the role of human judgment in the final decision.