Resources Courses 2018-06-11T14:25:56+00:00

Complexity Theory Course (17)

  • Wolfram Science Summer School

    Wolfram Science Summer School
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    A unique opportunity to do original research at the frontiers of science, the Wolfram Science Summer School helps about 40 students from a diverse range of scientific backgrounds learn about Stephen Wolfram's A New Kind of Science (NKS) and apply it to their fields of interest. Most of these students are advanced undergraduates and early graduate students, but those in different circumstances are considered. We are looking for students who want to move their careers in the NKS direction.

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  • Understanding Complexity

    Understanding Complexity
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    Recent years have seen the introduction of concepts from the new and exciting field of complexity science that have captivated the attention of economists, sociologists, engineers, businesspeople, and many others.

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  • Summer Complexity and Modeling Program

    Summer Complexity and Modeling Program
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    or nearly 30 years, the Santa Fe Institute has challenged and equipped the next generation’s brightest scholars to take on complex problems through schools, fellowships, and youth educational curricula serving students and educators of all ages and backgrounds. SFI Complexity Scholarship programs include instruction by, and interaction with, SFI scientists. Complexity scholars trained at the Santa Fe Institute are working to understand the theoretical foundations and patterns underlying the systems most critical to our future -- economies, ecosystems, conflict, disease, human social institutions, and the global condition. This intensive two-week residential science Summer CAMP introduces participants to complexity science scholarship.

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  • Principles of Complex Systems

    Principles of Complex Systems
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    Many of the problems we face in the modern world revolve around comprehending, controlling, and designing multi-scale, interconnected systems. Networked systems, for example, facilitate the diffusion and creation of ideas, the physical transportation of people and goods, and the distribution and redistribution of energy. Complex systems such as the human body and ecological systems are typically highly balanced, flexible, and robust, but also susceptible to systemic collapse. These complex problems almost always have economic, social, and technological aspects.

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  • Model Thinking

    Model Thinking
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    We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies.

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  • MIT Open Courseware: Networks, Complexity and Its Applications

    MIT Open Courseware: Networks, Complexity and Its Applications
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    Networks are a ubiquitous way to represent complex systems, including those in the social and economic sciences. The goal of the course is to equip students with conceptual tools that can help them understand complex systems that emerge in both nature and social systems. This is a course intended for a general audience and will discuss applications of networks and complexity to diverse systems, including epidemic spreading, social networks and the evolution of economic development.

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  • Masters in Complex Systems and Data Science (MS in CSDS)

    Masters in Complex Systems and Data Science (MS in CSDS)
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    Our Masters in Complex Systems and Data Science (CSDS) trains emerging data scientists to find, model, understand, and tell the stories of the patterns they uncover. 2. Our coursework comprises a balanced core of Complex Systems and Data Science and includes choose-your-own adventure options. 3. The Masters may be earned as a two year stand-alone degree or in one year as part of an Accelerated Masters for UVM undergraduate students.

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  • MSc Network Science

    MSc Network Science
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    Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. The goal of network science is to develop tools to analyse Big Data of interacting complex networks and to propose numerical and analytical frameworks to predict their behaviour

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  • Master of Complex Systems

    Master of Complex Systems
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    This 1.5-2 year program will provide you with the expertise to model, analyse and design resilient technological, socio-economic and socio-ecological systems as well as develop strategies for crisis forecasting and management.

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  • Master and Doctoral Programs in Complexity Sciences

    Master and Doctoral Programs in Complexity Sciences
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    A new curriculum for the Doctoral Program in Complexity Sciences has been approved, in July 2015, by the Portuguese Ministry of Education and Science. The new curriculum comprehends a 1st curricular year and a 2nd and 3rd years mainly dedicated to research at PhD level. (Lisbon)

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  • Name Graduate Certificate in Nonlinear and Complex Systems

    Name Graduate Certificate in Nonlinear and Complex Systems
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    The purpose of the certificate is to broaden the scope of the typical disciplinary graduate student traning program. Students are encouraged to develop interdisciplinary and transferable sets of skills in their course work and research activities. The certificate program helps to guide students toward this broad view by requiring the completion of: a survey course (CNCS 201, Topics in Nonlinear and Complex Systems ); four courses from an approved list; and a Ph.D. dissertation on a topic in the domain of the Center. In addition, the student must have two members of the Center on her or his Ph.D. dissertation committee.

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  • Complex Systems Graduate Certificate

    Complex Systems Graduate Certificate
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    The Center for the Study of Complex Systems (CSCS) and the Horace H. Rackham School of Graduate Studies at the University of Michigan are pleased to offer a Certificate of Graduate Studies in Complex Systems. This interdisciplinary curriculum, leading to a Graduate Certificate in Complex Systems, will introduce students to the ideas and methods used in the study of complex, nonlinear and adaptive systems. The specific aim of this curriculum is to allow students from different fields to integrate the rich paradigms and useful analytic and modeling techniques of complex systems into their own research.

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  • Complex Systems Summer School

    Complex Systems Summer School
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    The Complex Systems Summer School offers an intensive 4-week introduction to complex behavior in mathematical, physical, living, and social systems. The school is for graduate students, postdoctoral fellows, and professionals seeking to transcend traditional disciplinary boundaries and ask big questions about real-life complex systems.

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  • Complex Systems Modeling, Networks, and Data Analytics

    Complex Systems Modeling, Networks, and Data Analytics
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    The course will cover the basic construction and analysis of models including identifying what is to be modeled, constructing a mathematical representation, analysis tools and implementing and simulating the model in a computer program. Particular attention will be paid to choosing the right level of detail for the model, testing its robustness, and discussing which questions a given model can or cannot answer.

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  • Complex Adaptive Systems Science

    Complex Adaptive Systems Science
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    Complex adaptive systems (CASS) science is the study of highly interactive and dynamic systems that change over individual and evolutionary time scales. The spread of epidemics, society-biology interactions of obesity, impacts of agriculture on land degradation, ecological impacts of urban growth and social responses to natural disasters all involve CAS. Human societies have made the modern world more complex than ever before, with over 6 billion individuals living in urban centers of millions of inhabitants, divided into innumerable social and economic roles and organized into hierarchies many levels deep.

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  • Complex Adaptive Systems Masters Program

    Complex Adaptive Systems Masters Program
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    Complex Adaptive Systems (CAS) is an international, interdisciplinary master program at Chalmers University of Technology and the University of Gothenburg in Gothenburg, Sweden. The program is open to international and domestic students with a basic academic degree in the natural, engineering, or mathematical sciences. The focus is to use recently developed methods from complexity science to analyze a wide range of systems. Courses include computer simulations of complex systems, game theory, computational biology, robotics and much more.

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  • MSc in Network Science at Queen Mary University of London

    MSc in Network Science at Queen Mary University of London
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    Network Science is a very active and rapidly evolving research field with high societal impact, which stands at the crossroads of graph theory, complexity and data analysis. The goal of network science is to develop tools to analyse Big Data of interacting complex networks and to propose numerical and analytical frameworks to predict their behaviour.

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Systems Theory Course (2)

  • Systems Science Graduate Program

    Systems Science Graduate Program
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    Systems Science Graduate Program Systems Science is the study and application of general methods of problem solving and general principles governing systems of widely differing types. Systems Science is the study of general principles governing systems of widely differing types, and the use of systems ideas and methods in interdisciplinary research and socio-technical system design and management. Systems science draws on the natural and social sciences, mathematics, computer science, and engineering to address complex problems in the public and private sectors.

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  • Graduate Programs in Systems Science at Binghamton University

    Graduate Programs in Systems Science at Binghamton University
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    The Systems Science graduate program at Binghamton University offers a unique, internationally recognized, highly transdisciplinary learning and research experience that provides you with concepts, principles and methods for understanding, modeling, analyzing, optimizing and improving various forms of complex systems. Such systems thinking and problem solving skills will be an invaluable asset when you blaze a new trail in any scientific, engineering, business, or management profession, within today's increasingly complex world.

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Social Complexity Course (3)

  • Social and Economic Networks: Models and Analysis

    Social and Economic Networks: Models and Analysis
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    Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.

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  • PhD Program in Complex Systems and Brain Sciences

    PhD Program in Complex Systems and Brain Sciences
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    Complex Systems and Brain Scientists use mathematical models and experimental measurements to study the mechanisms that underlie complex behavior in systems from molecules and cells to the brain and groups of people. This new knowledge deals with the functioning of the normal brain, the treatment of neurological diseases, and possible rehabilitation, from early childhood to old age.

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  • Graduate Workshop in Computational Social Science

    Graduate Workshop in Computational Social Science
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    The workshop will bring together a group of advanced graduate students and a small faculty for an intensive two week study of computational social science modeling and complexity. The workshop will consist of lectures by faculty, special topic seminars by members of the Santa Fe Institute, and presentations of work in progress by graduate student participants. The primary goal of the summer workshop is to assist graduate students pursuing research agendas which includes a computational modeling component. A significant portion of the workshop will be devoted to analyzing and improving research being conducted by the graduate student participants.

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Complexity Economics course (1)

  • Oxford Summer School in Economic Networks

    Oxford Summer School in Economic Networks
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    The Oxford Summer School in Economic Networks will bring together students from a range of disciplines for a week to learn about the techniques, applications and impact of network theory in economics and development. We will have globally leading experts guide lectures and interactive workshops on topics such as social networks, games and learning, financial networks, economic complexity and urban systems.

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Systems Ecology course (2)

  • MIT Open Courseware: Modeling Environmental Complexity

    MIT Open Courseware: Modeling Environmental Complexity
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    Course Description: This course provides an introduction to the study of environmental phenomena that exhibit both organized structure and wide variability — i.e., complexity. Through focused study of a variety of physical, biological, and chemical problems in conjunction with theoretical models, we learn a series of lessons with wide applicability to understanding the structure and organization of the natural world. Students will also learn how to construct minimal mathematical, physical, and computational models that provide informative answers to precise questions.

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  • Dynamics of Complex Systems: Complexity in Ecology

    Dynamics of Complex Systems: Complexity in Ecology
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    Course Description: In this class we will critically review both classical works and recent literature on complexity in ecology. The emphasis will be on developing quantitative theories in the context of experimental and observational data. We will meet twice weekly for roundtable discussions.

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Complexity Management Course (2)

  • Decision Making in a Complex Uncertain World

    Decision Making in a Complex Uncertain World
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    This course will teach you the first principles of complexity, uncertainty and how to make decisions in a complex world. 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. After introducing the first principles, guest lecturers will cover interdisciplinary aspects of complexity. These are graph theory and networks, emergent behavior, agent-based modeling, evolutionary dynamics, cellular automata and self-organization, 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.

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  • Managing complexity: A systems approach – introduction

    Managing complexity: A systems approach – introduction
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    Do you need to change the way you think when faced with a complex situation? This free course, Managing complexity: A systems approach introduction, examines how systemic thinking and practice enables you to cope with the connections between things, events and ideas. By taking a broader perspective complexity becomes manageable and it is easier to accept that gaps in knowledge can be acceptable.

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Systems Design Course (2)

  • System Design & Management Masters MIT

    System Design & Management Masters MIT
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    Through the System Design & Management (SDM) core course and individually chosen electives, SDM fellows: learn to use systems thinking to understand the technical, managerial, and societal components of large-scale, complex challenges; discover how these components influence each other as part of larger systems; participate in rigorous classroom assignments and projects; learn to see the world and relationships in new ways; and innovate and lead from this inclusive and holistic view.

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  • MSc Complex Systems Engineering and Management

    MSc Complex Systems Engineering and Management
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    Are you looking for a Master's degree programme in which you learn to design in complex technical environments? But do you want more than ‘just’ technical skills? For example, do you want to look beyond the design of electric vehicles and concentrate on what is needed to implement electric transportation on a large scale? And therefore work on regulations, logistics, behavioural change, financial incentives etc.

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Systems Thinking Courses (1)

  • Systems Thinking and Complexity

    Systems Thinking and Complexity
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    Systems thinking provides theory and practical tools for seeking solutions to messy social and organisational problems at local, regional and global levels. A system’s behaviour emerges from interactions between its elements. Systems thinking starts with qualitative diagrams but as the number of elements, relations and feedback loops increases we need the computational approach of complex systems science

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Nonlinear Systems Courses (2)

  • Chaos

    Chaos
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    It has been called the third great revolution of 20th-century physics, after relativity and quantum theory. But how can something called chaos theory help you understand an orderly world? What practical things might it be good for? What, in fact, is chaos theory? "Chaos theory," according to Dr. Steven Strogatz, Director of the Center for Applied Mathematics at Cornell University, "is the science of how things change."

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  • Nonlinear Differential Equations: Order and Chaos

    Nonlinear Differential Equations: Order and Chaos
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    Phenomena as diverse as the motion of the planets, the spread of a disease, and the oscillations of a suspension bridge are governed by differential equations. MATH226x is an introduction to the mathematical theory of ordinary differential equations. This course follows a modern dynamical systems approach to the subject. In particular, equations are analyzed using qualitative, numerical, and if possible, symbolic techniques.

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Adaptive Systems Courses (1)

  • Master's Program Complex Adaptive Systems

    Master's Program Complex Adaptive Systems
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    The aim of this programme is to provide a broad and thorough introduction to the theory of complex systems and its applications to the world around us. The programme is based on a physics perspective with a focus on general principles, but it is also interdisciplinary with courses available in information theory, computer science and optimisation algorithms, ecology and genetics as

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Nonlinear Physics Course (2)

  • Nonlinear Dynamics and Chaos MIT

    Nonlinear Dynamics and Chaos MIT
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    This graduate level course focuses on nonlinear dynamics with applications. It takes an intuitive approach with emphasis on geometric thinking, computational and analytical methods and makes extensive use of demonstration software.

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  • Nonlinear Dynamics: Mathematical and Computational Approaches

    Nonlinear Dynamics: Mathematical and Computational Approaches
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    This course provides a broad introduction to the field of nonlinear dynamics, focusing both on the mathematics and the computational tools that are so important in the study of chaotic systems. The course is aimed at students who have had at least one semester of college-level calculus and physics, and who can program in at least one high-level language

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