About this course
We deal with a plethora of complex problems, such as why inequality is increasing? Do racial teams have greater decision-making abilities?, How can we predict the outcomes of elections?, and many others. In order to confront such complexity, we need to use models. Whether you work with science, business, policymaking, or even art, you will confront complex problems in different forms and contexts. Thinking in models will significantly help you comprehend and make the best use of data available for you to predict, understand, and develop the systems you are working with.
The course offers an introduction to modeling complex systems. It highlights different modeling approaches and several examples to study. Furthermore, the course introduces interactions systems as a key component of complex systems and explains how these can influence the emergent behaviors.
Learning outcomes
After successful completion of this course, students are expected to be able to:
- identify complexity in own research problems;
- develop a background on different approaches for modeling complex systems;
- understand interaction models and their role in complex systems;
- model and analyze complex systems.
Required prior knowledge
Assumed Knowledge:
Affinity with modeling and simulation
Link to more information
- CreditsECTS 6
- Levelbachelor
- Contact coordinator