Databricks-Generative-AI-Engineer-Associate試験無料問題集（63題）「Databricks Certified Generative AI Engineer Associate 認定」

出題：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. Headaches can be tough. Hope you feel better soon!

B. Please call your local emergency services.

C. Here are a few relevant articles for your browsing. Let me know if you have questions after reading them.

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

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：2

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?

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

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：3

A Generative Al Engineer has already trained an LLM on Databricks and it is now ready to be deployed.
Which of the following steps correctly outlines the easiest process for deploying a model on Databricks?

A. Save the model along with its dependencies in a local directory, build the Docker image, and run the Docker container

B. Wrap the LLM's prediction function into a Flask application and serve using Gunicorn

C. Log the model as a pickle object, upload the object to Unity Catalog Volume, register it to Unity Catalog using MLflow, and start a serving endpoint

D. Log the model using MLflow during training, directly register the model to Unity Catalog using the MLflow API, and start a serving endpoint

正解：D 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：4

A Generative AI Engineer I using the code below to test setting up a vector store:

Assuming they intend to use Databricks managed embeddings with the default embedding model, what should be the next logical function call?

A. vsc.create_delta_sync_index()

B. vsc.similarity_search()

C. vsc.create_direct_access_index()

D. vsc.get_index()

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：5

A Generative AI Engineer wants to build an LLM-based solution to help a restaurant improve its online customer experience with bookings by automatically handling common customer inquiries. The goal of the solution is to minimize escalations to human intervention and phone calls while maintaining a personalized interaction. To design the solution, the Generative AI Engineer needs to define the input data to the LLM and the task it should perform.
Which input/output pair will support their goal?

A. Input: Online chat logs; Output: Buttons that represent choices for booking details

B. Input: Customer reviews; Output: Classify review sentiment

C. Input: Online chat logs; Output: Cancellation options

D. Input: Online chat logs; Output: Group the chat logs by users, followed by summarizing each user's interactions

正解：A 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

出題：6

A Generative AI Engineer is developing an LLM application that users can use to generate personalized birthday poems based on their names.
Which technique would be most effective in safeguarding the application, given the potential for malicious user inputs?

A. Ask the LLM to remind the user that the input is malicious but continue the conversation with the user

B. Implement a safety filter that detects any harmful inputs and ask the LLM to respond that it is unable to assist

C. Increase the amount of compute that powers the LLM to process input faster

D. Reduce the time that the users can interact with the LLM

正解：B 解答を投票する

解説: (GoShiken メンバーにのみ表示されます)

Databricks-Generative-AI-Engineer-Associate試験無料問題集「Databricks Certified Generative AI Engineer Associate 認定」