Unlock the potential of knowledge graphs and RAG systems in this comprehensive course. Begin by setting up your development environment and configuring tools like the OpenAI API. You'll explore fundamental concepts of knowledge graphs, their structure, and their critical role in data systems. These early modules provide a strong foundation, ensuring you're ready for hands-on applications and more advanced topics. Moving forward, you’ll dive into practical implementation using Neo4j, a popular graph database. You’ll learn to construct and manage knowledge graphs, create entities and relationships, and execute complex queries to extract meaningful insights. Each lesson is designed to build your skills step-by-step, offering real-world scenarios to deepen your understanding. By the end of this section, you’ll be equipped to handle knowledge graphs effectively in diverse projects. The course then focuses on integrating knowledge graphs with RAG systems to enhance AI applications. You’ll master techniques such as vector indexing and embedding creation for efficient data retrieval. The final project brings everything together, enabling you to build a complete GraphRAG system. This course offers a thorough journey into a cutting-edge area of AI and data science, equipping you with the expertise to innovate and lead in your field.