[asme-dtm] NECSI Courses in Complexity

  • From: Seth Orsborn <sdo004@xxxxxxxxxxxx>
  • To: "asme-dtm@xxxxxxxxxxxxx" <asme-dtm@xxxxxxxxxxxxx>
  • Date: Fri, 22 Nov 2013 14:51:58 -0500

NECSI Courses in Complexity
Winter Session 2014
The winter session offers two intensive week-long courses. The courses consist 
of lectures, discussions, and supervised group projects. Though the second week 
builds on material covered in the previous week, CX201 is not a prerequisite 
for CX202. You may register for either or both weeks. If desired, arrangements 
for credit at a home institution may be made in advance.


Dates: January 6 - 17, 2014

Location: MIT, Cambridge, MA

Week 1: January 6-10 CX201: Complex Physical, Biological and Social Systems

Lab: January 12 CX102: Computer Programming and Complex Systems

Week 2: January 13-17 CX202: Complex Systems Modeling and Networks

Registration: http://necsi.edu/education/school.html?action=reg 

Who Attends

These courses are intended for faculty, graduate students, post-doctoral 
fellows, professionals and others who would like to gain an understanding of 
the fundamentals of complex systems for application to research in their 
respective fields, or as a basis for pursuing complex systems research.


Excellent course...useful thematic overview... applications in diverse contexts 
were exciting. Particularly appreciated the group project - excellent 
experiential pedagogy.

The course was an eye-opening framework to analyze my work through a different 

Presentations were extremely useful for me in understanding how to begin 
modeling complex systems and assessing them. Helped me understand a lot of 
things I have been doing so far without clearly understanding the principles.

This class very much stretched my mind to apply the ideas of complexity to the 
world... I believe I learned more on a grander scale... will help enrich my 
vocabulary and the way of thinking in the world with respect to complexity.

CX201: Complex Physical, Biological and Social Systems
Dates: January 6-10, 2014

This course offers an introduction to the essential concepts of complex systems 
and related mathematical methods and simulation strategies with application to 
physical, biological and social systems. The course will particularly focus on 
the use of multiscale representations as a unifying approach to complex systems 
concepts, methods and applications.

Concepts to be discussed include: emergence, complexity, networks, 
self-organization, pattern formation, evolution, adaptation, fractals, chaos, 
cooperation, competition, attractors, interdependence, scaling, dynamic 
response, information, and function.

Methods to be discussed include: statistical methods, cellular automata, 
agent-based modeling, pattern recognition, system representation and 


CX102: Computer Programming and Complex Systems
Date: January 12, 2014

This course introduces computer programming in the Python language for those 
with little or no computer programming experience. It is designed as a 
precursor to CX202.

The course will present programming concepts and hands-on exercises. Topics to 
be covered include: data structures, algorithms, variables and assignments, 
numerical and logical operations, lists and dictionaries, user-defined 
functions, flow control, loops, and visualization.


CX202: Complex Systems Modeling and Networks
Dates: January 13-17, 2014

This course provides (a) an introduction to building models of complex systems 
(physical, biological, social and engineered), and (b) the study of networks, 
including topologies and dynamics of real world networks.

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.

The study of networks will introduce the use of network topologies and the 
characterization of networks describing complex systems, including such 
concepts as small worlds, degree distribution, diameter, clustering 
coefficient, modules, and motifs. Different types of network topologies and 
network behaviors that model aspects of real complex systems will be described 
including: modular, sparse, random, scale-free, influence, transport, 
transformation, and structure.

NOTE: Students without a background in programming are strongly recommended to 
attend CX102: Computer Programming and Complex Systems in conjunction with 


For more information and registration, visit:

Other related posts:

  • » [asme-dtm] NECSI Courses in Complexity - Seth Orsborn