Overview

Master AI engineering from fundamentals to production. This hands-on guide transforms you into a job-ready AI engineer across 43 carefully structured chapters - perfect for interviews at top companies and building real-world AI systems.WHAT MAKES THIS BOOK DIFFERENT: - Every chapter includes working code you can run immediately- 43 custom diagrams visualize complex concepts clearly- Production-focused - learn how real AI systems are built, not just theory- Three complete end-to-end projects included- Written by a practicing AI Researcher, not just a theoristWHAT YOU WILL LEARN: FOUNDATIONS (Chapters 1-10)Streaming APIs, LangChain basics, Memory management, Vector databases with ChromaDB, Retrieval-Augmented Generation (RAG), AI Agents with ReAct pattern, Model Context Protocol (MCP), PyTorch fundamentals, Prompt Engineering, and the Hugging Face ecosystem.ADVANCED FRAMEWORKS (Chapters 11-20)CrewAI for multi-agent teams, AutoGen, Microsoft Copilot Studio, LangGraph for advanced workflows, LlamaIndex, Google Vertex AI, Google ADK, Fine-Tuning with LoRA, Advanced RAG (hybrid search, reranking, RAGAS), and MLOps with MLflow and LangSmith.PRODUCTION AND ENTERPRISE Cloud AI platforms (Azure OpenAI, AWS Bedrock, IBM WatsonX), Multimodal AI, Deep Learning with Transformers, NLP techniques, Advanced AI Agents with Memory and Human-in-the-Loop, Data Engineering, Responsible AI, Emerging Research (GraphRAG, Long Context, Mixture of Experts), Computer Vision, and Function Calling.

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