Knowledge Graphs for Enterprise AI: Neo4j, LLMs & GraphRAG

About this course

This course contains the use of artificial intelligence to narrate the audios. The reason for this decision - AI narration voice used is better quality than even human voice and the speed of production was much faster! However, the content of the course has been compiled and 100% reviewed by Bashir Ahmed, the creator of this course.

Knowledge Graphs for Enterprise AI: A Practical GuideUnlock the power behind the world's most intelligent AI systems. Knowledge graphs are the secret infrastructure driving enterprise search, recommendation engines, and next-generation RAG pipelines — and now you can build them too.

In this hands-on course, you'll go from zero to production-ready, learning how to model complex real-world data as connected knowledge, query it with SPARQL and Cypher, and wire it into LLM-powered applications that actually understand context.

Whether you're an AI engineer looking to supercharge your retrieval pipelines, a data architect designing smarter systems, or a developer curious about how companies like Google, Amazon, and Microsoft structure knowledge at scale — this course gives you practical skills you can apply on Monday morning.

What you'll walk away with:

• A working knowledge graph built from real enterprise dataLLM integrations that use graph context for richer, more accurate answers
• Confidence to design and deploy KG-backed AI solutions at work

No PhD required. Just curiosity and a willingness to think in connections. Relational databases no longer enough to power up enterprise AI Agentic solutions, you need knowledge graphs! If you are a solution architect or data engineer or LLM developer, this course is a must, and it can supercharge your career!

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