DS 8104 - Network Science

Effective Date 09/28/2022
Networks provide a unifying framework to study the structure hidden within complex data. This graduate-level course focuses on the fundamental concepts and statistics as well as recent advancements and applications of network science. Topics include: graph theory, structural paradoxes, measures and algorithms for quantifying importance, community detection, network inference, recommendation systems, and link prediction.

Credits: 3
Grading Basis Graded
Requisites Must be a Data Science PhD student