Graph-to-Graph Algorithms and Transformations

Graphs are the natural language for representing complex relationships, from social networks to molecular structures. Understanding how to map, translate, and transform one graph structure into another is a critical skill in modern computer science and data engineering. This text-only course guides you through the foundational concepts of graph theory, representation, and graph-to-graph algorithms, helping you build a strong conceptual framework. Learn to analyze network topologies, apply transformation algorithms, and understand how graph structures are manipulated in modern software systems. What you'll learn: Understand foundational graph theory concepts, terminology, and representation formats; Apply core graph traversal and transformation algorithms to modify network topologies; Learn the principles of graph-to-graph translation and mapping techniques; Explore modern graph representation learning and the basics of Graph Neural Networks (GNNs); Practice structural manipulation through written exercises and step-by-step conceptual walkthroughs. You will start with essential definitions and basic graph structures before progressing to advanced structural transformations and modern representation techniques. This course is designed for beginners in computer science, data analysis, or software engineering, with no advanced mathematical prerequisites required. Begin reading today to master the mechanics of graph-to-graph transformations.