NODES 2025 - From Air Quality to Aircraft and Automobiles, Data Is Everywhere

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9 learners

What you'll learn

This course includes

51.3 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

neo4j graph databases graphs LLM retrieval augmented generation RAG vector database vector search GenAI AI Artificial intelligence nodes25

Full Transcript

Tim Spann explores how Apache NiFi can be used to integrate open source LLMs to implement scalable and efficient RAG pipelines. He shows how any kind of data including graph, semi-structured, structured, and unstructured data from a variety of sources and types can be processed, queried, and used to feed large language models for smart, contextually aware answers. Look for his example utilizing Cortex AI, LLAMA, Apache NiFi, Apache Iceberg, Snowflake, open source tools, libraries, and Notebooks. Tim will integrate NiFi, Snowflake and Neo4j Graph Data Science. Speaker: Timothy Spann Resources: Get Started with Aura - https://bit.ly/3LOLrjh Deployment Center - https://bit.ly/4jOelM3 Ground AI Systems and Agents with Neo4j - https://bit.ly/4oVsnyb #nodes2025 #neo4j #graphdatabase #graphrag #knowledgegraph