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 OpenAI

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.