Agentic AI by Aravind choudhary

Agentic AI is a practical and comprehensive guide designed for students, developers, AI enthusiasts, and professionals who want to understand and build intelligent AI systems capable of reasoning, planning, using tools, and completing complex tasks autonomously. The book begins with the fundamentals of Agentic AI and Large Language Models (LLMs) and gradually progresses to advanced concepts such as AI agents, tool calling, memory, Retrieval-Augmented Generation (RAG), workflows, human-in-the-loop systems, and multi-agent architectures. With a hands-on and project-oriented approach, readers will learn how to build AI agents that can interact with external tools, retrieve information, make decisions, execute multi-step tasks, and collaborate with other agents to solve real-world problems. What You Will Learn Introduction to Artificial Intelligence Introduction to Generative AI What is Agentic AI? Generative AI vs Agentic AI AI Agents and Intelligent Systems Large Language Models (LLMs) LLM-Based Applications Prompt Engineering Agent Architecture Reasoning and Planning Tool Calling and Function Calling Agent Memory Short-Term and Long-Term Memory Retrieval-Augmented Generation (RAG) Embeddings and Vector Databases LangChain Fundamentals Building Agents with LangChain LangGraph Fundamentals Graph-Based AI Workflows State Management in Agents ToolNode and Agent Workflows Human-in-the-Loop Systems Middleware and Agent Control Multi-Agent Systems Agent Collaboration Autonomous AI Workflows AI Agent Evaluation Error Handling and Reliability AI Agent Security Building AI Agent Applications with Python Real-World Agentic AI Projects Who This Book Is For This book is suitable for: AI and Agentic AI beginners BCA, MCA, B.Tech, and computer science students Python developers Software developers Generative AI and LLM learners Aspiring AI Engineers Machine Learning and Data Science learners Developers interested in AI Agents Students preparing for AI and Generative AI interviews Anyone interested in building autonomous AI applications