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CMPLXSYS 335 - Introduction to Complex Systems

This course will introduce the use of computational and data-driven methods to studynetworked systems including social networks, information networks, and biologicalnetworks, with applications to a range of network-driven phenomena in data science,online interaction, web search, epidemiology, network resilience, opinion formation, andother areas.

There are networks in every part of our lives: the Internet and the web, social networks,neural networks, the power grid, the road network, ecological networks, biochemicalnetworks, and many others. The field of network science deals with mathematical andcomputational methods for the analysis and understanding of networked systems likethese. This course will introduce the fundamental tools of the field through lectures andhands-on experience with analysis, modeling, and interpretation of networks andnetwork data. Students will be introduced to fundamental concepts of network sciencesuch as centrality measures (“Which of these web sites is most relevant to your searchquery?”), network connectivity (“How can we design the network of airline routes to getpassengers to their destinations as quickly as possible?”), and dynamics (“How far andhow fast will this disease spread within the community?”) Students will learn themathematical fundamentals of the field and then employ them in the form ofcomputational and mathematical models and develop software for processing large-
scale network data to extract new knowledge and engage in network problem solving ina wide range of areas.


Meets distribution Requirement: MSA

Meets General Requirements: BS; QR/1