Listed in: Computer Science, as COSC-355
Matteo Riondato (Section 01)
Many phenomena can be represented as networks of interactions between different components. Network science is the discipline at the intersection of computer science, statistics, and physics that studies the structure, formation, evolution, and behavior of such networks, with the goal of understanding the phenomena they represent.
In this course we study algorithmic, computational, and statistical approaches to the analysis of networks of people (both online and offline), web pages, proteins, and physical goods. We cover, among other topics: models of network formation, ways of measuring the importance of entities in networks and algorithms to calculate those metrics, models and algorithms for diffusion of information and diseases, and human-friendly approaches for visualizing network dynamics.
Requisite: COSC 211, and one of COSC 223, MATH 360 or STATS 360, or consent of the instructor. Limited to 50 students. Fall semester. Assistant Professor Riondato.
How to handle overenrollment: Priority to majors
Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: TBA
M 02:00 PM - 03:20 PM SCCE A331
W 02:00 PM - 03:20 PM SCCE A331
|A First Course in Network Science||Cambridge University Press, 2021||F. Menczer, S. Fortunato, and C. A. Davis||Optional Reading||TBD|
|Network Science||Cambridge University Press, 2015||A. L. Barabasi||Optional Reading||TBD|