Course topics
- Introduction
- Theory of graphs and complex networks
- Random graphs
- Software for graph analysis
- Property of no scale
- Barabasi-Albert Model
- Evolutionary models of networks
- The importance of nodes
- The notion of centrality
- Stability and vulnerability of networks to accidental crashes and targeted attacks
- Tasks of finding clusters
- Modularity
- Processes on networks
- The spread of viruses and ideas, the model of thinking in society
Prerequisites
- Statistics and Econometrics
- Linear Algebra for Data Science
- Differential and integral calculus
- Combinatorics
- Fundamentals of the theory of graphs