دانلود کتاب راهنمای مطالعه برای مدرک «مهندس هوش مصنوعی مولد (سطح مقدماتی)» دیتابریکس (Databricks)

Generative AI is reshaping how organizations interact with data, build applications, and deliver intelligence across the enterprise. What began as experimentation with large language models is quickly evolving into a new application paradigm in which models reason over trusted data, automate complex workflows, and support decision making at scale. As this transition accelerates, the challenge for practitioners is no longer simply understanding how foundation models work. The real opportunity lies in learning how to connect those models to enterprise data, evaluate their behavior, govern their usage, and deploy them reliably in production environments. Certifications such as the Databricks Certified Generative AI Associate play an important role in preparing engineers and data professionals for this shift. Rajaniesh Kaushikk is a Databricks MVP and Databricks Champion. His book provides a practical and well-structured guide to those capabilities. It brings together the essential concepts required to understand generative AI on the Databricks Data Intelligence Platform and presents them in a way that connects certification objectives with implementation patterns used in real-life across modern organizations. Readers are introduced not only to the mechanics of LLMs but also to RAG, vector search, evaluation strategies, and model lifecycle practices that enable production-ready solutions. The book emphasizes the relationship between models and governed enterprise data. Great generative AI systems are built by combining models with reliable data pipelines, scalable infrastructure, and strong governance frameworks. Platforms that unify data, analytics, and AI make this possible, and those who understand this integration will help shape the next generation of intelligent applications. Rajaniesh’s vast experience as a practitioner and educator is evident throughout. He approaches genAI as part of a broader architectural shift toward data intelligence platforms that enable organizations to move from experimentation to production with confidence. This perspective makes the book valuable not only for certification candidates but also for engineers and architects who want to understand how generative AI solutions are designed and deployed responsibly at scale. Wherever you are on your journey with generative AI on Databricks— whether you are just starting out, or seeking to strengthen your expertise through certification—this book provides a timely and practical foundation for building the next generation of data-driven AI applications.