6.7260
Network Science and Models
Introduces the main mathematical models used to describe large networks and dynamical processes that evolve on networks. Static models of random graphs, preferential attachment, and other graph evolution models. Epidemic propagation, opinion dynamics, social learning, and inference in networks. Applications drawn from social, economic, natural, and infrastructure networks, as well as networked decision systems such as sensor networks.
Prerequisites & course information
Prereq: 6.3702 and 18.06 G (Spring) 3-0-9 units
Sources
- Course catalogue ↗2026–2027