Interactive Graph Theory Lessons (learngraphtheory.org)

A new interactive learning platform brings graph theory to life with step-by-step visualizations of 23+ core graph algorithms, designed for students, educators, and professionals. Users can watch dynamic node coloring and edge highlighting as algorithms run, follow structured lessons with hands-on exercises, and access tailored lesson plans, language translations, custom branding, and LMS integration. The offering also supports bespoke algorithm implementations and curriculum-specific sequences, making it easy to adapt to courses or corporate training programs. This matters for the AI/ML community because graphs underpin many modern models and problems—network analysis, influence propagation, community detection, route optimization, and biological or financial network modeling. Visualizing algorithm behavior helps demystify complexity (e.g., traversal order, shortest-path relaxations, flow augmentations, and clustering steps), aids debugging and implementation of efficient data structures, and accelerates intuition for graph neural networks and other graph-based methods. By bridging theory and practice with customizable, animated lessons, the platform can improve pedagogy, speed up onboarding for research teams, and make it easier to translate algorithmic insights into real-world system design and optimization.