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xviii, 352 pages : illustrations ; 24 cm
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Includes index
"As generative AI becomes central to modern data and machine learning workflows, earning the Databricks Certified Generative AI Engineer Associate certification demonstrates both technical credibility and practical fluency. This study guide prepares you for the exam with clear, comprehensive coverage of core GenAI and LLM concepts, data management using Delta Lake, and retrieval-augmented generation (RAG) workflows on the Databricks platform. Drawing on author Rajaniesh Kaushikk's experience in enterprise architecture, generative AI, and modern data platforms, this book combines hands-on labs, real-world examples, and exam-aligned guidance to help you design, build, and deploy effective GenAI applications. From prompt engineering and RAG-based solutions to model governance with Unity Catalog, MLflow tracking, and Hugging Face model integration, this guide supports both your certification preparation and real-world AI development. Understand the fundamentals of generative AI, LLMs, and vector databases; Prepare and manage large-scale data using Delta Lake and the data lakehouse architecture; Build, track, and deploy GenAI applications with Databricks and MLflow; Apply RAG patterns to improve response quality, relevance, and grounding; Implement responsible AI practices and model governance with Unity Catalog."--