In this hands-on course, you will use the knowledge gained in the Neo4j & LLM Fundamentals course to convert unstructured text content and turn it a Knowledge Graph that can be queried through natural language using GPT-4’s Cypher generation.
This course relies heavily on the information contained in the Neo4j & LLM Fundamentals course. If you have not already done so, we recommend completing this course first.
We also assume a basic understanding of Python. It is not necessary, but you may also benefit from taking the Building Neo4j Applications with Python course to understand how the Neo4j Python Driver works.
What you will learn
How to construct a Knowledge Graph using unstructured data
How Langchain agents can be used to improve the responses from LLMs
Retrieval Augmented Generation (RAG)
Langchain Agents and QA Chains
If you find yourself stuck at any stage then our friendly community will be happy to help. You can reach out for help on the Neo4j Community Site, or head over to the Neo4j Discord server for real-time discussions.
If you have any comments or feedback on this course you can email us on email@example.com.
Course Coming Soon
We are currently working on this course. Fill in the form below to register your interest and we will contact you when it is ready.