Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
Complexity science: an introducton
Rating: 4.1 out of 5(31 ratings)
240 students
Last updated 2/2015
English

What you'll learn

  • The aim of this course is to give you an overview to the main areas of complexity science

Course content

6 sections13 lectures2h 8m total length
  • Complexity science: an overview5:08

    The definition to complexity science is still very much open to debate, for some it means the study of nonlinear systems, to others it is simply a form of interdisciplinary science. In this video we present the history of complexity science as it has emerged out of modern science and present a definition of it as the application of complexity theory to the study of the complex systems in our world such as financial networks, cities, ecosystems amongst many others

  • Complexity science digging deeper15:00

    This lesson will dig deeper into some of the concepts that were introduced in the first lesson on complexity science

  • Complexity science quiz

Requirements

  • There are no prerequisites to this course (though some prior knowledge of complexity theory would be of great benifit) aside for a firm grasp of the english language and a basic level of general scientific knowledge

Description

Complexity Science is a science for the complex world we live in at the turn of the 21st century, by using new theories that let us look at age old problems with a fresh perspective and leveraging the use of powerful computation and large data sets it is offering us new insight into the fundamental workings of our interconnected world of networks, globalization and sustainability.

This course gives an overview to the emerging new area of science that is complexity science. By applying the tools of complexity theory such as network analysis, systems theory and self organization, complexity science studies the complex systems in our world that have traditionally been some what overlooked, such as chaotic weather patterns, social networks, transportation systems or the spread of pandemics, to name just a few. This course will cover some of the main applications of complexity theory to various scientific, domains such as:

Social network analysis is the application of network theory and the tools of data analysis to the modeling of social systems. With the arrival of high-powered computing and the proliferation of data sets relating to social interaction, social network analysis is taking off.

Earth systems science is the study of earth as a complex adaptive system. Inherently interdisciplinary it crosses the scientific boundaries to treat the earth as an integrated system. This section introduces you to the application of complexity theory to the modeling and analysis of our planet.

Complexity economics is part of a new set of ideas surrounding economic theory, it sees the economy as a complex system evolving over time through the interaction of multiple adaptive elements that give rise to the emergent structures of enterprises and whole markets.

Complex technology systems are large networks composed of multiple highly interconnected technologies, such as electrical power grids, telecommunication networks, transportation networks or global supply chains. The organization of these systems involves a web of connections and demonstrates self-driven adaptability and emergence behaviour. The tools of complexity theory are beginning to be applied to modeling these technologies and helping us to get a better understanding of their operations.

Who this course is for:

  • This course is intended for a broad group of people but will be particularly relevant for those with a background in a technical domain such a some area of math, science, engineering or business