Udemy
Agentic AI, Generative AI, LLMs, RAG & MCP
Artificial Intelligence · Data Science · Development
Library / Artificial Intelligence
On Udemy
Prepare for Databricks Certified Generative AI Engineer Associate with five complete timed practice exams and 225 original scenario questions. Each exam contains 45 questions and allows 90 minutes, reflecting the published scored-question count and time limit. The real exam may also include unidentified unscored items.
Every practice exam covers all six official domains: Design Applications, Data Preparation, Application Development, Assembling and Deploying Applications, Governance, and Evaluation and Monitoring. Each uses the same whole-question allocation of 6, 6, 14, 10, 4 and 5. This is a rounded approximation of the official 14%, 14%, 30%, 22%, 8% and 12% weights, not a claim that fractional questions can appear.
Practice choosing appropriate components, preparing and retrieving evidence, diagnosing agent behavior, packaging and deploying applications, governing access, and evaluating quality and cost. Scenarios include RAG, AI Search, MLflow, Unity Catalog, prompt management, MCP tools, authentication, and human feedback. Questions distinguish exam-guide terminology from current product names and explicitly scope legacy deployment scenarios.
Every option has an explanation showing why it is accepted or rejected. Each question includes direct official supporting documentation so you can inspect the evidence behind the answer. Both single-answer and clearly identified multiple-selection questions are included.
Attempt a complete test before reading its explanations. Use missed objectives to guide focused documentation study and hands-on practice. The 80% passing setting is an instructor-selected practice benchmark, not an official Databricks passing score, certification guarantee, or prediction of exam results.
This is a practice-test course, not a video curriculum, executable lab environment or exact reproduction of the proctored exam interface.
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Udemy: 2026-10-22 · Coursera: 2026-10-22 · O'Reilly: 2026-10-22 · 365 Data Science: 2026-10-22
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