January 6-10

This course provides an introduction to (a) essential concepts of complex systems and related mathematical methods and simulation strategies with application to physical, biological and social systems, and (b) the fundamentals of data analytics, machine learning, and artificial intelligence.

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 informatics.

Demonstration of the application of complex systems methods will be made through studies of:

• Social systems: education system, health care system, military system

• Psychosocial systems: patterns of social behavior, mind, creativity

• Biological systems: physiology, brain, cellular systems, genetic networks

• Physical systems: meteorology

The data analytics lessons will cover skills needed to transform raw data into visualizations and insight. The course will cover fundamental 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.