Databricks GenAI Engineer Associate: Practice Tests

Turning an LLM demonstration into a dependable Databricks application involves more than choosing a model. You need to identify missing evidence, select tools that respect business constraints, package the application correctly, and distinguish evaluation results from production telemetry.

This independent English practice course contains 360 original questions across six tests. It targets the Databricks Certified Generative AI Engineer Associate exam guide effective March 18, 2026. The course addresses all six published domains, including Agent Bricks task selection, Genie integration, MCP tools, prompt lifecycle management, retrieval evaluation, deployment and monitoring.

A practical study path

• Test 1: 75 questions on design, source preparation and core decisions.
• Test 2: 75 questions on application development and retrieval diagnostics.
• Test 3: 60 questions on assembly, serving, persistent state and integration.
• Test 4: 60 questions on governance, evaluation and production monitoring.
• Tests 5 and 6: two distinct 45-question, 90-minute mocks with different decision conditions.

Every question includes feedback for each option, an explanation of the deciding conditions and a focused study suggestion. Scenarios ask you to compare realistic alternatives, diagnose failures and choose an appropriate response to evidence.

Use the feedback, not just the score

Work through the targeted tests first. For each missed item, identify the condition that rules out the nearest alternative. Then attempt each mock without notes and revisit weak decision types using the explanations and linked documentation.

The mock length and duration follow the official scored-item count and time limit. Their domain allocation approximates the published 14%, 14%, 30%, 22%, 8% and 12% weights. Detailed objective quotas and the single-answer item mix are author designed. The 80% practice threshold is a revision goal, not an official passing score or scaled-score conversion. Additional official unscored items are not modeled.

The official guide calls the retrieval service Vector Search; current documentation also calls it AI Search. Examples distinguish legacy serving endpoint behavior where it differs from newer Unity Gateway services. This course is a question-based study resource, not a video course or a hosted Databricks lab.

Independent preparation and AI disclosure

BrightRung Learning is independent of Databricks. This course is not endorsed by the certification provider and contains no claimed live examination questions or guaranteed outcomes. Certification names and marks identify the relevant study topic.

AI tools were used to draft and refine questions, explanations and the cover background. The same AI-assisted production process checked the content against official documentation and reviewed the written material. This is not a claim of independent human professional review. Use official documentation and your own hands-on practice alongside this resource.