GenAI Beyond Chat with RAG, Knowledge Graphs and Python

​We are excited to invite you to this in-person, 4-hour workshop in San Francisco. This is a great opportunity to learn about GenAI, RAG and Knowledge Graphs.

​Bring your laptop and build a RAG application along with our experts.
Space is limited. Food and drinks will be served.

​Workshop Agenda:

​10:00: Open door and registration
10:30: Welcome and Workshop, part 1
12:00: Lunch
13:00 - 15:30: Workshop, part 2
16:00: Closing

​Description:

​Learn how to integrate generative AI models using Python, Neo4j and Langchain.

​You will:

• ​Learn about Large Language Models (LLMs), hallucinations and integrating knowledge graphs

• ​Explore Retrieval Augmented Generation (RAG) and its role in grounding LLM generated content

• ​Use vector indexes and embeddings in Neo4j to perform similarity and keyword search

• ​Use Python and Langchain to integrate with Neo4j and Large Language Model

​After completing the workshop, you will have practical understanding of LLMs, RAG, and knowledge graphs. You will also have the skills to create simple LLM-based applications using Neo4j and Python.

​Prerequisites:

​Before taking this course, you should have:

• ​A basic understanding of Graph Databases and Neo4j

• ​Knowledge of Python and capable of reading simple programs

​We recommend taking the Neo4j Fundamentals course.