Data Analytics, Optimization and Prediction

The course explores how optimization and quantitative methods can be used to address decision-making problems in the digital economy. It introduces fundamental optimization techniques and selected prediction methods, while critically assessing their respective strengths and limitations. Students develop an understanding of the implications of different models for business decision-making and public policy.

The course will cover

• Fundamentamental concepts and principles of linear and nonlinear optimization

• Formulation and analysis of common optimization problems arising in business and economics

• Decision-making and resource allocation subject to constraints

• Selected algorithmic and heuristic solution methods

• Basic understanding on how predictions can support optimization and data-driven decision-making

• Discussion of strengths and limitations of different optimization approaches