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Databricks Certified Generative AI Engineer Associate

Verified practice questions with detailed answers, clear explanations, and community discussion.

  • 109

    questions

  • 4 days ago

    last updated

  • 4.8/5

    overall rating

Question 1 of 109

A Generative Al Engineer has created a RAG application to look up answers to questions about a series of fantasy novels that are being asked on the author’s web forum. The fantasy novel texts are chunked and embedded into a vector store with metadata (page number, chapter number, book title), retrieved with the user’s query, and provided to an LLM for response generation. The Generative AI Engineer used their intuition to pick the chunking strategy and associated configurations but now wants to more methodically choose the best values.

Which TWO strategies should the Generative AI Engineer take to optimize their chunking strategy and parameters? (Choose two.)

Answer choices
Show answer

Correct answers: C, E

Systematic chunk optimization requires evaluating retrieval or answer quality against representative questions rather than relying on intuition. Metrics such as recall or NDCG measure whether relevant passages are retrieved, allowing paragraph-, section-, or chapter-based chunking approaches to be compared objectively. An LLM-as-a-judge can also assess how well the retrieved chunk supports the expected answer, capturing relevance and usefulness that simple token counts cannot. Changing embedding models or adding query classification may improve the overall RAG system, but they do not directly determine the best chunking parameters.

Community votes

10 votes

CESuggested

100%

Question 2 of 109

A Generative AI Engineer is designing a RAG application for answering user questions on technical regulations as they learn a new sport.

What are the steps needed to build this RAG application and deploy it?

Answer choices
Show answer

Correct answer: B

A RAG application first ingests and indexes regulation documents into a vector search system so relevant context can be found semantically. At query time, the application retrieves the most relevant document chunks and supplies them to the LLM, which generates a grounded answer. The completed retrieval-and-generation workflow is then evaluated for quality, relevance, and correctness before deployment through Model Serving. Evaluating before the response-generation workflow is established would not test the complete application.

Community votes

13 votes

BSuggested

92%

C

8%

Question 3 of 109

A Generative AI Engineer just deployed an LLM application at a digital marketing company that assists with answering customer service inquiries.

Which metric should they monitor for their customer service LLM application in production?

Answer choices
Show answer

Correct answer: A

Number of customer inquiries processed per unit of time measures the application’s production throughput and ability to handle real customer demand. Monitoring this metric helps identify capacity constraints, traffic changes, and performance issues that could delay customer support responses. Training perplexity is a model-development metric, while leaderboard values and energy usage do not directly show whether the deployed service is processing customer requests effectively.

Community votes

9 votes

ASuggested

100%

Question 4 of 109

A Generative AI Engineer is building a Generative AI system that suggests the best matched employee team member to newly scoped projects. The team member is selected from a very large team. The match should be based upon project date availability and how well their employee profile matches the project scope. Both the employee profile and project scope are unstructured text.

How should the Generative Al Engineer architect their system?

Answer choices
Show answer

Correct answer: D

A vector store enables semantic matching between unstructured project scopes and employee profiles, capturing meaning beyond exact keyword overlap. Team profiles are embedded once and retrieved using the project scope as the query, which scales efficiently for a very large team. Availability is handled through filtering after the date-based tool identifies eligible employees, ensuring only available candidates are considered. Embedding project scopes instead would reverse the retrieval relationship and does not efficiently identify the best employee for a new project.

Community votes

11 votes

DSuggested

64%

C

36%

Question 5 of 109

A Generative AI Engineer is designing an LLM-powered live sports commentary platform. The platform provides real-time updates and LLM-generated analyses for any users who would like to have live summaries, rather than reading a series of potentially outdated news articles.

Which tool below will give the platform access to real-time data for generating game analyses based on the latest game scores?

Answer choices
Show answer

Correct answer: C

Feature Serving provides low-latency access to up-to-date features, such as current game scores and live statistics, for real-time inference. The LLM-powered commentary platform can retrieve these continuously updated values while generating summaries and analyses. Foundation Model APIs supply model access but do not provide live data, while AutoML focuses on building predictive models rather than serving current features.

Community votes

10 votes

CSuggested

90%

B

10%

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Charles Sirois
Canada
As this was my first certification exam, I was understandably nervous about what to expect. These study materials made the preparation process much easier, and many of the questions closely reflected those on the actual exam.
Lance Chambers
United States
Wasted about a month going through the free dump sites scattered all over reddit, half the answers were wrong and the other half were for a version of the exam that doesn't even exist anymore. Eventually gave in and paid the small fee here, and the difference was night and day.
Alisha Kelly
Italy
Honestly, I had already gone through the official documentation quite thoroughly, but still didn't feel fully confident going in. This helped things finally click for me. I realized I knew the material, but just hadn't connected all the pieces yet.
Casper Claassen
Netherlands
Used this along with Microsoft Learn and the combo worked really well. The practice questions made the stuff I'd read actually stick. Passed first attempt, no complaints from me.
Gabriele Ghesla
Italy
The content is accurate and clearly presented, and it's more affordable than competitors. The team has been incredibly responsive whenever I've had an issue, and they've been open to small changes that improve the platform.
Morgan Farmer
United Kingdom
I don't usually leave reviews, but this one felt worth sharing. The questions were quite close to what actually appeared on the exam, more than I expected. I spent about a week going through the material before my test, and it helped me feel more prepared.
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I had a smooth experience from start to finish. Access was available right away, no technical issues, which made it easy to get started. The content felt relevant and aligned well with what I was looking for.
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Does what it says it does. Content felt solid, nothing confusing to navigate and I didn't run into any weird issues. I been putting off scheduling the exam for a while and going through this gave me enough confidence to finally book it and pass.
Neil Savage
United States
A very quick response was received via email when a link issue occurred. The study materials provided were high quality and extremely helpful. I was able to complete the test successfully. Many thanks for the excellent support.
Morgan Farmer
United Kingdom
I don't usually leave reviews, but this one felt worth sharing. The questions were quite close to what actually appeared on the exam, more than I expected. I spent about a week going through the material before my test, and it helped me feel more prepared.
Remi Nuyts
United States
Passed ITIL 4 Foundation with 87%. Material was enough by itself.
Archie Hopkins
United States
I had a smooth experience from start to finish. Access was available right away, no technical issues, which made it easy to get started. The content felt relevant and aligned well with what I was looking for.
Nancy Mcbride
United States
Does what it says it does. Content felt solid, nothing confusing to navigate and I didn't run into any weird issues. I been putting off scheduling the exam for a while and going through this gave me enough confidence to finally book it and pass.
Neil Savage
United States
A very quick response was received via email when a link issue occurred. The study materials provided were high quality and extremely helpful. I was able to complete the test successfully. Many thanks for the excellent support.

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