Databricks GenAI Engineer Associate Exam Preparation

About this course

This course contains the use of artificial intelligence.

Prepare for the Databricks Certified Generative AI Engineer Associate exam with a course built around the six official exam domains at their published weightings, with the heaviest coverage on Application Development (30 percent) and Assembling and Deploying Applications (22 percent) - exactly where the exam concentrates its questions.

This is a hands-on platform course, not a generic GenAI overview. Every concept is grounded in the specific Databricks tools the exam tests: you will design compound AI applications, prepare data and chunking strategies for retrieval, build RAG applications with Databricks Vector Search, construct multi-stage chains and agents with LangChain, log and register them with MLflow, deploy with Model Serving and Foundation Model APIs, govern assets with Unity Catalog and AI guardrails, and evaluate deployed apps with MLflow LLM evaluation and Lakehouse Monitoring. Labs are notebook-style walkthroughs you can follow in a Databricks workspace, from creating a Vector Search index over a Delta table to serving and monitoring a complete RAG chain.

Taught by Aseem Mankotia (TechNuggets Academy). Every chapter includes exam callouts flagging what Databricks actually tests, common traps to avoid, and scenario-based practice questions in the style of the real exam. Two full-length practice tests with 90 scenario questions and detailed explanations round out your preparation, and the final chapter walks through a complete 45-question exam simulation with strategy for the 90-minute format.

Databricks recommends six months of hands-on experience with generative AI solutions before sitting the exam; this course assumes working Python and SQL plus basic ML familiarity.

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