A user types: "Can you explain how to set up a Databricks cluster?" What is the user's intent?

To ask for a comparison of cluster types.

To complain about a cluster setup issue.

To request a step-by-step explanation or instructions on cluster setup.

To request a code snippet for cluster creation.

A user writes: 'I want to cancel my subscription, but first tell me if there's a cheaper plan.' A retention bot needs to handle this. What is the best augmentation strategy?

Extract only the user's current plan and treat the entire input as a plan inquiry.

Identify two intents: 'cancel subscription' and 'plan inquiry', extract the user's current plan, and structure the prompt to address both.

Ask the user to choose one request at a time.

Identify only the 'cancel subscription' intent and ignore the plan inquiry.

A team is building a multilingual customer support bot. When a user writes in Spanish, the baseline LLM responds in English. The team wants the bot to respond in the same language as the user. Which augmentation strategy is most effective?

Use a separate model for each language.

Add a general instruction to 'respond in the user's language' without detecting the language.

Use a translation API to translate the user's input to English before sending it to the LLM.

Detect the language of the user's input and add an instruction to respond in that language, along with the detected language as context.

A team is building a chatbot that should answer questions about a company's HR policies. The baseline LLM gives accurate but overly long answers. The team wants concise answers that still include all key points. Which prompt adjustment is most effective?

Add the instruction 'Provide a concise summary that includes all key points' and provide an example of a concise summary.

Add the constraint 'Maximum 50 words' without an example.

Increase the temperature to 0.8 to make the response more varied.

Use the baseline response because it is accurate.

A research assistant is asked: 'What are the environmental impacts of lithium mining in Chile?' The team wants to retrieve relevant academic papers. Which term extraction is most appropriate for the search query?

Extract 'lithium mining', 'environmental impacts', and 'Chile' as the key terms.

Extract 'environmental' and 'mining' as the key terms.

Extract 'what', 'are', and 'the' as the key terms.

Extract only 'Chile' as the key term.

DatabricksCertified Generative AI Engineer Associate

Domain 3Objective 2

Prompt Engineering and Augmentation GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions (Page 3)

Part of the Section 3: Application Development domain, which makes up ~18% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~6–11 in this domain), expect 1–2 from this objective — we provide 31 practice questions to prepare you well beyond it. (estimate)

31questions here

7free pages

8concepts

Questions 11–15

11foundation · easy
A user types: "Can you explain how to set up a Databricks cluster?" What is the user's intent?
Select an answer first
12expert · hard
A user writes: 'I want to cancel my subscription, but first tell me if there's a cheaper plan.' A retention bot needs to handle this. What is the best augmentation strategy?
Select an answer first
13expert · hard
A team is building a multilingual customer support bot. When a user writes in Spanish, the baseline LLM responds in English. The team wants the bot to respond in the same language as the user. Which augmentation strategy is most effective?
Select an answer first
14expert · hard
A team is building a chatbot that should answer questions about a company's HR policies. The baseline LLM gives accurate but overly long answers. The team wants concise answers that still include all key points. Which prompt adjustment is most effective?
Select an answer first
15expert · hard
A research assistant is asked: 'What are the environmental impacts of lithium mining in Chile?' The team wants to retrieve relevant academic papers. Which term extraction is most appropriate for the search query?
Select an answer first

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