Building AI Agents with LLMs, RAG, and Knowledge Graphs: A practical guide to autonomous and modern AI agents amzn.to/4n146Gg Master LLM fundamentals to advanced techniques like RAG, reinforcement learning, and knowledge graphs to build, deploy, and scale intelligent AI agents that reason, retrieve, and act autonomously What you will learn - Learn how LLMs work, their structure, uses, and limits, and design RAG pipelines to link them to external data - Build and query knowledge graphs for structured context and factual grounding - Develop AI agents that plan, reason, and use tools to complete tasks - Integrate LLMs with external APIs and databases to incorporate live data - Apply techniques to minimize hallucinations and ensure accurate outputs - Orchestrate multiple agents to solve complex, multi-step problems - Optimize prompts, memory, and context handling for long-running tasks - Deploy and monitor AI agents in production environments

@Python_Dv Intriguing. Scaling intelligent AI agents presents both exciting potential and complex challenges. What unforeseen societal impacts might arise?

@Python_Dv Love this practical guide—RAG, knowledge graphs, and live data integration are exactly where AI agents shine. Looking forward to seeing how you deploy and monitor these in production.