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  3. Introduction to Complexity

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:

Course structure

  1. What is Complexity?
  2. Dynamics and Chaos
  3. Fractals
  4. Information, Order, and Randomness
  5. Genetic Algorithms
  6. Cellular Automata
  7. Models of Biological Self-Organization
  8. Models of Cooperation in Social Systems
  9. Networks
  10.  Scaling in Biology and Society
  • Teacher:
    Melanie Mitchell
    Melanie Mitchell
    Professor at Portland State University, External Professor at the Santa Fe Institute
  •  
    Santiago Guisasola
    Santiago Guisasola
    Postdoctoral Researcher at the Instituto Nacional de Matemática Pura e Aplicada
  •  
    Leonid Chechurin
    Leonid Chechurin
    Professor at LUT University
  • University:
    Santa Fe Institute
    USA
    Santa Fe Institute

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