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Databricks Databricks-Generative-AI-Engineer-Associate: Databricks Certified Generative AI Engineer Associate

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Question 1

A Generative AI Engineer is developing a patient-facing healthcare-focused chatbot. If the patient??s question is not a medical emergency, the chatbot should solicit more information from the patient to pass to the doctor??s office and suggest a few relevant pre-approved medical articles for reading. If the patient??s question is urgent, direct the patient to calling their local emergency services.
Given the following user input:
??I have been experiencing severe headaches and dizziness for the past two days.?? Which response is most appropriate for the chatbot to generate?

A. Here are a few relevant articles for your browsin

B. Let me know if you have questions after reading them.

C. Please call your local emergency services.

D. Headaches can be toug

E. Hope you feel better soon!

F. Please provide your age, recent activities, and any other symptoms you have noticed along with your headaches and dizziness.

Correct Answer:B

Question 2

When developing an LLM application, it??s crucial to ensure that the data used for training the model complies with licensing requirements to avoid legal risks.
Which action is NOT appropriate to avoid legal risks?

A. Reach out to the data curators directly before you have started using the trained model to let them know.

B. Use any available data you personally created which is completely original and you can decide what license to use.

C. Only use data explicitly labeled with an open license and ensure the license terms are followed.

D. Reach out to the data curators directly after you have started using the trained model to let them know.

Correct Answer:D

Question 3

A Generative Al Engineer is developing a RAG application and would like to experiment with different embedding models to improve the application performance.
Which strategy for picking an embedding model should they choose?

A. Pick an embedding model trained on related domain knowledge

B. Pick the most recent and most performant open LLM released at the time

C. pick the embedding model ranked highest on the Massive Text Embedding Benchmark (MTEB) leaderboard hosted by HuggingFace

D. Pick an embedding model with multilingual support to support potential multilingual user questions

Correct Answer:A

Question 4

A Generative AI Engineer has a provisioned throughput model serving endpoint as part of a RAG application and would like to monitor the serving endpoint??s incoming requests and outgoing responses. The current approach is to include a micro-service in between the endpoint and the user interface to write logs to a remote server.
Which Databricks feature should they use instead which will perform the same task?

A. Vector Search

B. Lakeview

C. DBSQL

D. Inference Tables

Correct Answer:D

Question 5

A Generative AI Engineer is tasked with deploying an application that takes advantage of a custom MLflow Pyfunc model to return some interim results.
How should they configure the endpoint to pass the secrets and credentials?

A. Use spark.conf.set ()

B. Pass variables using the Databricks Feature Store API

C. Add credentials using environment variables

D. Pass the secrets in plain text

Correct Answer:C

Question 6

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.)

A. Change embedding models and compare performance.

B. Add a classifier for user queries that predicts which book will best contain the answe

C. Use this to filter retrieval.

D. Choose an appropriate evaluation metric (such as recall or NDCG) and experiment with changes in the chunking strategy, such as splitting chunks by paragraphs or chapter

E. Choose the strategy that gives the best performance metric.

F. Pass known questions and best answers to an LLM and instruct the LLM to provide the best token coun

G. Use a summary statistic (mean, median, etc.) of the best token counts to choose chunk size.

H. Create an LLM-as-a-judge metric to evaluate how well previous questions are answered by the most appropriate chun

I. Optimize the chunking parameters based upon the values of the metric.

Correct Answer:CE

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