SYSEN 6172

SYSEN 6172

Course information provided by the 2026-2027 Catalog.

This course provides students with modern network science concepts and mathematical/computational tools for modeling and analysis of various complex networks in both their structures and dynamics. Specific topics to be discussed include; mathematical analysis of network structures and dynamics, statistical properties of complex networks, dynamics *of* networks and dynamics *on* networks, co-evolutionary adaptive networks, epidemic thresholds and phase transitions in networks, temporal networks, multiplex/multilayer networks, higher-order networks, and applications to real-world complex systems problems. Python and NetworkX will be used as the primary tools for network modeling and analysis, in addition to other computational tools introduced and used as needed. Students should have a reasonable amount of experience in Python programming and linear algebra.


Last 4 Terms Offered (None)

Learning Outcomes

  • Conduct advanced network modeling, analysis and simulation using appropriate mathematical/computational means.
  • Design and conduct original research using network science methods and tools.
  • Demonstrate integration of Systems Engineering knowledge and techniques and advanced network science skills in the form of a final project.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Opt NoAud

  •  8989 SYSEN 6172   LEC 001

    • TR
    • Jan 25 - May 11, 2027
    • Sayama, H

  • Instruction Mode: In Person

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Opt NoAud

  •  8990 SYSEN 6172   LEC 002

    • Jan 25 - May 11, 2027
    • Sayama, H

  • Instruction Mode: Distance Learning-Asynchronous