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Databricks Databricks-Generative-AI-Engineer-Associate Exam With Confidence Using Practice Dumps

Exam Code:
Databricks-Generative-AI-Engineer-Associate
Exam Name:
Databricks Certified Generative AI Engineer Associate
Certification:
Vendor:
Questions:
61
Last Updated:
Apr 26, 2025
Exam Status:
Stable
Databricks Databricks-Generative-AI-Engineer-Associate

Databricks-Generative-AI-Engineer-Associate: Generative AI Engineer Exam 2025 Study Guide Pdf and Test Engine

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Databricks Certified Generative AI Engineer Associate Questions and Answers

Question 1

A Generative Al Engineer is deciding between using LSH (Locality Sensitive Hashing) and HNSW (Hierarchical Navigable Small World) for indexing their vector database Their top priority is semantic accuracy

Which approach should the Generative Al Engineer use to evaluate these two techniques?

Options:

A.

Compare the cosine similarities of the embeddings of returned results against those of a representative sample of test inputs

B.

Compare the Bilingual Evaluation Understudy (BLEU) scores of returned results for a representative sample of test inputs

C.

Compare the Recall-Onented-Understudy for Gistmg Evaluation (ROUGE) scores of returned results for a representative sample of test inputs

D.

Compare the Levenshtein distances of returned results against a representative sample of test inputs

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Question 2

A Generative Al Engineer wants their (inetuned LLMs in their prod Databncks workspace available for testing in their dev workspace as well. All of their workspaces are Unity Catalog enabled and they are currently logging their models into the Model Registry in MLflow.

What is the most cost-effective and secure option for the Generative Al Engineer to accomplish their gAi?

Options:

A.

Use an external model registry which can be accessed from all workspaces

B.

Setup a script to export the model from prod and import it to dev.

C.

Setup a duplicate training pipeline in dev, so that an identical model is available in dev.

D.

Use MLflow to log the model directly into Unity Catalog, and enable READ access in the dev workspace to the model.

Question 3

A Generative Al Engineer would like an LLM to generate formatted JSON from emails. This will require parsing and extracting the following information: order ID, date, and sender email. Here’s a sample email:

They will need to write a prompt that will extract the relevant information in JSON format with the highest level of output accuracy.

Which prompt will do that?

Options:

A.

You will receive customer emails and need to extract date, sender email, and order ID. You should return the date, sender email, and order ID information in JSON format.

B.

You will receive customer emails and need to extract date, sender email, and order ID. Return the extracted information in JSON format.

Here’s an example: {“date”: “April 16, 2024”, “sender_email”: “sarah.lee925@gmail.com”, “order_id”: “RE987D”}

C.

You will receive customer emails and need to extract date, sender email, and order ID. Return the extracted information in a human-readable format.

D.

You will receive customer emails and need to extract date, sender email, and order ID. Return the extracted information in JSON format.