Introduction to Complexity
In this course you'll learn about the tools used by scientists to understand complex systems. The topics you'll learn about include dynamics, chaos, fractals, information theory, self-organization, agent-based modeling, and networks. You’ll also get a sense of how these topics fit together to help explain how complexity arises and evolves in nature, society, and technology. There are no prerequisites. You don't need a science or math background to take this introductory course; it simply requires an interest in the field and the willingness to participate in a hands-on approach to the subject.
The course can be take under the instruction of the authors Prof. Melanie Mitchell and Santiago Guisasola from Santa Fe Institute (USA) or with instructor Prof. Leonid Chechurin from LUT University (Finland).
Learning outcomes
Upon successful completion of the course the learner is expected to be able to:
- develop the model of large-scale socio-technical problems
- simulate the complex models of socio-technical problems
- analyse the behavior of complex systems
Course structure
- What is Complexity?
- Dynamics and Chaos
- Fractals
- Information, Order, and Randomness
- Genetic Algorithms
- Cellular Automata
- Models of Biological Self-Organization
- Models of Cooperation in Social Systems
- Networks
- Scaling in Biology and Society
