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Education

A multidisciplinary approach to complex systems

Education

Education in complex systems involves a wide variety of topics including, but not limited to: agent-based modeling, social networks, nonlinear dynamics, cellular automata, artificial life, global systems, robustness, scaling laws, social dynamics, markets, communication, human language, behavior, biological computation, cognitive neuroscience, and adaptive computation.

NICO 101

Introduction to Programming for Big Data

The skills needed to go from data to knowledge and application are in high demand. This course provides an introduction to the foundational skills needed by data scientists.

Courses

NICO faculty engage in undergraduate, graduate, and executive education on the topics of networks and complex systems. Representative courses taught by NICO faculty and other courses related to NICO interests are listed below. Courses numbered 395 and 495 are taught on an experimental basis, often being assigned permanent course numbers later.

Undergraduate

Undergraduate

  • Introduction to Programming for Big Data (NICO 101-0)
  • Introduction to Dynamical Systems (ESAM 322)
  • Introduction to Complex Networks (ESAM 395)
  • Introduction to Complex Systems (ESAM 395)
  • Introduction to Computational Neuroscience (ESAM 370)
  • Introduction to Feedback Systems (EECS 360)
  • Introduction to Digital Control (EECS 374)
  • Nonlinear Dynamics and Chaos (PHYS 371)
  • Computational Biology: Principles and Applications (ChBE 379)
  • Modeling Soft Matter: Networks, Membranes, and Fluctuations (ESAM 321)
  • Designing and Constructing Models with Multi-Agent Languages (EECS 372)
  • Process Dynamics and Control (ChBE 341)
  • Sustainability, Technology, and Society (ChBE 365)
  • Language Evolution (LING 243)
  • Words, Networks, and the Internet (LING 336)
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Graduate

Graduate

  • System Theory (EECS 410)
  • Design of Technologies for Learning (Learning Sciences 426)
  • Nonlinear Dynamics and Chaos (PHYS 430)
  • Social Network Analysis (IEMS 441)
  • Social Dynamics and Networks (Kellogg, MORS 945)
  • Models in Applied Mathematics (ESAM 421)
  • Numerical Methods for Random Processes (ESAM 448)
  • Designing and Constructing Models with Multi-Agent Languages (EECS 472)
  • Introduction to Computational Research (ChBE 495)
  • Dynamical Processes on Networks (ESAM 495)
  • Mathematical Epidemiology (ESAM 495)
  • Nonlinear Control (ME 495)
  • Introduction to Computational Neuroscience (ESAM 495)
  • Words, Networks, and the Internet (LING 336)
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NICO Reading Group

Discuss the latest research in complex systems.

The Northwestern Institute for Complex Systems Reading Group is for interested researchers (internal or external to Northwestern) who have an interest in complex systems.

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