Atlas of Knowledge is an open, machine-readable representation of university-level knowledge. I built it around a structured hierarchy of disciplines, courses, topics, concepts, prerequisites, relationships, and applications rather than simply collecting documents or reproducing textbooks and lecture material. The project combines auditable provenance, deterministic dataset generation, knowledge-graph relationships, licensing gates, validation infrastructure, and structured educational records. It is designed for educational retrieval, knowledge graphs, dataset research, and carefully evaluated machine-learning workflows.