Module 2 introduces graph theory, beginning with its origins in the "Seven Bridges of Königsberg" problem. It then covers basic terminology, defining core components like nodes, edges, loops, and arcs , as well as node metrics such as degree, degree sequence, and degree distribution. The module explores fundamental graph properties for classification, including directionality, weightedness, and multi-graphs. Subsequently, various idealized graph models are presented, such as complete, star, cycle, small-world, and scale-free graphs, to analyze network structures. We conclude by explaining two methods for representing graphs mathematically: the adjacency matrix and the memory-efficient adjacency list.