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Starting with the basics of Generative AI and LLMs, you'll learn how to work with prompts, models, output parsers, document loaders, text splitters, embeddings, vector databases, Retrieval-Augmented Generation (RAG), tools, memory, and agents. The book then introduces LangGraph, where you'll discover how to design stateful workflows, implement conditional routing, create multi-agent systems, manage persistence with checkpoints, and build scalable AI applications.
Through practical examples and real-world projects, you'll develop AI-powered chatbots, document question-answering systems, research assistants, customer support agents, code assistants, workflow automation solutions, and multi-agent applications. Every chapter emphasizes hands-on coding using Python and the latest LangChain and LangGraph ecosystem.
Whether you're preparing for AI interviews, developing enterprise AI solutions, or building your own AI startup, this book provides the knowledge and practical skills required to create reliable and production-ready Agentic AI applications.
What You Will Learn
Fundamentals of Generative AI and Large Language Models
Prompt Engineering techniques and best practices
LangChain architecture and core components
Working with Chat Models and Prompt Templates
Output Parsers and Structured Output
Document Loaders and Text Splitters
Embeddings and Vector Databases
Retrieval-Augmented Generation (RAG)
AI Tools and Function Calling
Memory Management in AI Applications
AI Agents with LangChain
LangGraph fundamentals and graph architecture
StateGraph, Nodes, Edges, and State Management
Conditional and Iterative Workflows
Persistence, Checkpoints, and Durable Execution
Human-in-the-Loop Applications
Multi-Agent Systems and Agent Collaboration
Building Production-Ready AI Applications
Integrating OpenAI, Gemini, Mistral, Hugging Face, Ollama, and other LLM providers
Best Practices for Performance, Scalability, and Deployment
Yana
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Muallif haqida
Arvind Choudhary is an experienced Software Developer, Corporate Trainer, and Technology Mentor from India with around 12 years of professional experience in the IT industry. He has worked extensively for 8 years as a developer and 4 years as a corporate trainer, helping students, professionals, and organizations build strong technical skills in modern software technologies.
He specializes in Java Full Stack Development, Python Full Stack Development, MERN Stack, Flutter, Android Development, Artificial Intelligence (AI), Machine Learning (ML), Generative AI, Agentic AI, AI Agents, and Android Firmware Development.
Throughout his career, Arvind Choudhary has trained and mentored numerous students and working professionals through live projects, practical implementation, industry-focused training, and real-world application development. His teaching approach focuses on simplifying complex technical concepts into easy-to-understand practical learning experiences.
As an author and trainer, he is passionate about sharing knowledge in emerging technologies including Generative AI, AI Automation, Prompt Engineering, Large Language Models (LLMs), and modern software engineering practices. His goal is to help learners become industry-ready developers and technology innovators.
Arvind Choudhary continues to contribute to the technology community through technical training, content creation, software development, and educational initiatives focused on next-generation technologies.
