This course will teach you the first principles of complexity, uncertainty and how to make decisions in a complex world.
Leaders must be able to act in a complex world and under uncertainty. This course is a first step to develop yourself into one of the future’s key decision makers or to enhance your decision-making skills.
First, this course will address what complexity is and will define uncertainty. Next, we cover a number of tools and methods to understand and be able to navigate through the complex and uncertain world.
The need for a multidisciplinary approach will be emphasised throughout the course. Guest lecturers from different faculties will explain, provide applications and examples from their respective fields of study for a more comprehensive understanding of the different elements of complexity. For example, complexity can be beautifully explained by the use of insects and brains and many other natural and social phenomena. The same ideas can be applied to economic and financial systems.
After introducing the first principles, guest lecturers will cover interdisciplinary aspects of complexity. These are graph theory and networks, emergent behaviour, agent-based modeling, evolutionary dynamics, cellular automata and self-organisation, complexity in history, decision making under uncertainty, heuristics and biases and subsequently leadership and entrepreneurship. Finally, relating this all back together in two case studies will conclude the course. The first case study is financial stability and crises and the latter is growth and development of cities.
By completing this course you will have developed skills and knowledge that will enhance your decision-making skills in order to act in a complex world and under uncertainty. By taking part you will have the opportunity to purchase a Statement of Participation.
Anyone should be able to participate in course. However, basic knowledge of economic, financial institutions, mathematics and logic will be helpful. The course will be taught at undergraduate level.