Lilly Tech Systems
Learn AI Knowledge Management
Master the techniques for organizing, retrieving, and leveraging enterprise knowledge using AI. From knowledge graphs and RAG systems to intelligent search and organizational strategies — build systems that make information accessible and actionable.
Your Learning Path
Follow these lessons in order to build a complete understanding of AI-powered knowledge management.
1. Introduction
What is AI knowledge management? Why traditional approaches fail and how AI transforms information access.
2. Knowledge Graphs
Build and query knowledge graphs using AI. Entity extraction, relationship mapping, and graph databases.
3. RAG for Enterprise
Implement Retrieval-Augmented Generation for enterprise knowledge bases. Chunking, embedding, and retrieval strategies.
4. Search
AI-powered semantic search, hybrid search, re-ranking, and building intelligent search experiences.
5. Organization
Auto-tagging, classification, taxonomy generation, and AI-driven content organization strategies.
6. Best Practices
Production deployment, governance, data quality, evaluation metrics, and scaling knowledge systems.
What You'll Learn
By the end of this course, you'll be able to:
Build Knowledge Graphs
Create AI-powered knowledge graphs that capture entities, relationships, and context from unstructured data.
Implement Enterprise RAG
Deploy retrieval-augmented generation systems that give LLMs access to your organization's knowledge.
Power Intelligent Search
Build semantic search systems that understand intent and return relevant results across all content types.
Organize at Scale
Use AI to automatically classify, tag, and organize knowledge assets for easy discovery.