Building AI Agents with LLMs, RAG, and Knowledge Graphs

Part 1: The AI Agent Engine: From Text to Large Language Models

This part lays the foundation for understanding how modern AI agents process and generate language. It begins by exploring how raw text can be represented in numerical form suitable for deep learning models, introducing techniques such as word embeddings and basic neural architectures. The focus then shifts to the Transformer model and explains how attention mechanisms revolutionized natural language processing. Finally, it examines how large language models (LLMs) are built by scaling transformers, discussing training strategies, instruction tuning, fine-tuning, and the evolution toward models capable of general-purpose reasoning. Together, these chapters provide the technical ...