Databricks Certified Generative AI Engineer Associate Study Guide

Introduction

As generative AI becomes central to modern data and machine learning workflows, earning the Databricks Certified Generative AI Engineer Associate certification signals both credibility and technical fluency. This study guide prepares you for this sought-after certification with comprehensive coverage of core GenAI and LLM concepts, practical data management using Delta Lake, and retrieval-augmented generation (RAG) application workflows on the Databricks platform.

Author and Content

Written by AI expert Rajaniesh Kaushikk, this book combines hands-on labs, real-world examples, and exam-aligned content to help you build and deploy effective GenAI applications. From prompt engineering and RAG-based solutions to model governance with Unity Catalog, MLflow tracking, and leveraging Hugging Face models in GenAI workflows, this guide supports both your certification journey and real-world AI development.

Key Topics Covered

Understand the fundamentals of generative AI, LLMs, and vector databases

Prepare and manage large-scale data using Delta Lake and the data lakehouse

Build and deploy generative AI models with Databricks and MLflow

Explore RAG for enhanced model performance

Implement responsible AI practices and model governance with Unity Catalog