BİL489

School of Engineering \ Computer Engineering

3

6

Elective

Turkish

BİL331

Computer Engineering
Artificial Intelligence Engineering

This course introduces the fundamental concepts of graph theory, integrating classical topics such as connectivity and trees with modern insights from network science, including scale-free networks, small-world phenomena, and centrality measures, providing students with a comprehensive understanding of both theoretical foundations and real-world applications in complex network analysis.

Introduction to Graph Theory. Fifth Edition. By Robin J. Wilson. Pearson.
Network Science, A. L. Barabasi, Cambridge Press

Learning the fundamental concepts in graph theory, understanding the key properties of complex networks such as scale-free and small-world phenomena and their implications in real-world systems, and analyzing centrality measures and community structures to interpret the roles of nodes and relationships in complex systems.

1. Knowledge of main concepts and theorems in graph theory.
2. Understanding the structural properties and dynamic behaviors of complex networks, including scale-free and small-world networks.
3. Ability to analyze centrality measures and community structures to evaluate the roles of nodes and edges in complex systems.

Week 1: Introduction
Week 2: Graph Theory Concepts
Week 3: Graph Theory Concepts - 2
Week 4: Random Networks
Week 5: Scale-Free Property
Week 6: Barabasi-Albert Model
Week 7: Dynamic Networks
Week 8: Degree Correlations
Week 9: Network Robustness
Week 10: Communities in Networks
Week 11: Spread Effects and Epidemics
Week 12: Introduction to Learning in Networks