Introduction to Complex Networks

Lecture, Summer 26

This course offers a broad introduction to the field of network science, which studies complex networks such as social networks, biological systems, technological infrastructures, and information networks. Students will learn fundamental concepts from network theory and gain experience with computational tools for analyzing and visualizing networks. The course covers both theoretical foundations and practical skills needed to model, analyze, and interpret complex networked systems.

Topics Include:

• Basics of graph theory and algebraic network representations: nodes, edges, adjacency matrices
• Structural properties: degree distributions, clustering coefficients, path lengths
• Centrality measures: PageRank centrality, betweenness centrality, etc.
• Community detection and modularity
• Random graph models (Erdős–Rényi), small-world networks (Watts-Strogatz), scale-free networks (Barabási-Albert)
• Network motifs and subgraph patterns
• Dynamics on networks: epidemic spreading, diffusion processes
• Robustness and resilience of networks: attack tolerance vs. error tolerance
• Visualization techniques for large-scale networks
• Applications in sociology, biology, and the analysis of internet/web structure

Timetable

Lectures take place on Tuesdays and Wednesdays from 8:30 to 10:00 am in AH III and AH VI, respectively. Exercise sessions will be held on Mondays from 8:30 to 10:00 am in AH I. The exact schedule can be found in RWTHonline.