Use Neo4j’s query language Cypher to manage and retrieve data stored in knowledge graphs.
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Instructor: Andreas Kollegger
Use Neo4j’s query language Cypher to manage and retrieve data stored in knowledge graphs.
Write knowledge graph queries that find and format text data to provide more relevant context to LLMs for Retrieval Augmented Generation.
Build a question-answering system using Neo4j and LangChain to chat with a knowledge graph of structured text documents.
Knowledge graphs are used in development to structure complex data relationships, drive intelligent search functionality, and build powerful AI applications that can reason over different data types. Knowledge graphs can connect data from both structured and unstructured sources (databases, documents, etc.), providing an intuitive and flexible way to model complex, real-world scenarios.
Unlike tables or simple lists, knowledge graphs can capture the meaning and context behind the data, allowing you to uncover insights and connections that would be difficult to find with conventional databases. This rich, structured context is ideal for improving the output of large language models (LLMs), because you can build more relevant context for the model than with semantic search alone.
This course will teach you how to leverage knowledge graphs within retrieval augmented generation (RAG) applications. You’ll learn to:
After course completion, you’ll be well-equipped to use knowledge graphs to uncover deeper insights in your data, and enhance the performance of LLMs with structured, relevant context.
Anyone who wants to understand how knowledge graphs work, how to build with them, and create better RAG applications. We recommend familiarity with LangChain or taking LangChain: Chat with Your Data prior to this course.
Introduction
Knowledge Graph Fundamentals
Querying Knowledge Graphs
Preparing Text for RAG
Constructing a Knowledge Graph from Text Documents
Adding Relationships to the SEC Knowledge Graph
Expanding the SEC Knowledge Graph
Chatting with the Knowledge Graph
Conclusion
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