Introduction to systems thinking and systems analysis. Why model? Purposes of models, limitations of models, validation and calibration, uncertainty, model design. [“The art and craft of modeling”]
Simulation models. Systems dynamics. Agent-based models.
Optimization models. Linear and non-linear optimization. Stochastic optimization. Decision under uncertainty.
Network analysis and complexity science
Data modeling. Econometric models. Statistical inference.
Co-production of knowledge and participatory modelling.
Good OpenScience and OpenData practices.
Week 2 is reserved for team work. More details to follow.
Trainers
The course will be taught by experienced scientists from IIASA and partner organizations who have ample experience in developing and applying models to real-world problems. [details to be published soon]