Databricks Databricks-Generative-AI-Engineer-Associate Free Sample Exam Questions 2026

Here you can get the actual Databricks Databricks-Generative-AI-Engineer-Associate exam questions and answers in PDF for free and for all questions premium file. These best Databricks Certified Generative AI Engineer Associate Exam Databricks-Generative-AI-Engineer-Associate PDF questions are for every Databricks users. Real Databricks-Generative-AI-Engineer-Associate exam dumps that will assist you to crack the %certification% certification exam in the PDF format. For Advance preparation premium PDF files available for perfect exam preparation on reilable price option.

UNLOCK FULL
Databricks-Generative-AI-Engineer-Associate Exam Features

In Just $35 You can Access

• All Official Question Types
• Interactive Web-Based Practice Test Software
• No Installation or 3rd Party Software Required
• Customize your practice sessions (Free Demo)
• 24/7 Customer Support

Get Full Access

Page: 1 / 13
Total Questions: 61

Questions & Answers PDF

• Question 1

  

  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?

  • Input: Online chat logs; Output: Group the chat logs by users, followed by summarizing each user’s interactions
  • Input: Online chat logs; Output: Buttons that represent choices for booking details
  • Input: Customer reviews; Output: Classify review sentiment
  • Input: Online chat logs; Output: Cancellation options

  Reveal Answer Answer: B Next Question

• Question 2

  

  A Generative AI Engineer developed an LLM application using the provisioned throughput Foundation Model API. Now that the application is ready to be deployed, they realize their volume of requests are not sufficiently high enough to create their own provisioned throughput endpoint. They want to choose a strategy that ensures the best cost-effectiveness for their application.What strategy should the Generative AI Engineer use?

  • Switch to using External Models instead
  • Deploy the model using pay-per-token throughput as it comes with cost guarantees
  • Change to a model with a fewer number of parameters in order to reduce hardware constraint issues
  • Throttle the incoming batch of requests manually to avoid rate limiting issues

  Reveal Answer Answer: B Next Question

• Question 3

  

  A Generative Al Engineer interfaces with an LLM with prompt/response behavior that has been trained on customer calls inquiring about product availability. The LLM is designed to output “In Stock” if the product is available or only the term “Out of Stock” if not.Which prompt will work to allow the engineer to respond to call classification labels correctly?

  • Respond with “In Stock” if the customer asks for a product.
  • You will be given a customer call transcript where the customer asks about product availability. The outputs are either “In Stock” or “Out of Stock”. Format the output in JSON, for example:{“call_id”: “123”, “label”: “In Stock”}.
  • Respond with “Out of Stock” if the customer asks for a product.
  • You will be given a customer call transcript where the customer inquires about product availability. Respond with “In Stock” if the product is available or “Out of Stock” if not.

  Reveal Answer Answer: B Next Question

• Question 4

  

  What is the most suitable library for building a multi-step LLM-based workflow?

  • Pandas
  • TensorFlow
  • PySpark
  • LangChain

  Reveal Answer Answer: D Next Question

• Question 5

  

  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?

  • Here are a few relevant articles for your browsing. Let me know if you have questions after reading them.
  • Please call your local emergency services.
  • Headaches can be tough. Hope you feel better soon!
  • Please provide your age, recent activities, and any other symptoms you have noticed along with your headaches and dizziness.

  Reveal Answer Answer: B Next Question

• Question 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?

  • Implement a safety filter that detects any harmful inputs and ask the LLM to respond that it is unable to assist
  • Reduce the time that the users can interact with the LLM
  • Ask the LLM to remind the user that the input is malicious but continue the conversation with the user
  • Increase the amount of compute that powers the LLM to process input faster

  Reveal Answer Answer: A Next Question

• Question 7

  

  A Generative Al Engineer has developed an LLM application to option questions about internal company policies. The Generative AI Engineer must ensure that the application doesn’t hallucinate or leak confidential data.Which approach should NOT be used to mitigate hallucination or confidential data leakage?

  • Add guardrails to filter outputs from the LLM before it is shown to the user
  • Fine-tune the model on your data, hoping it will learn what is appropriate and not
  • Limit the data available based on the user’s access level
  • Use a strong system prompt to ensure the model aligns with your needs.

  Reveal Answer Answer: B Next Question

• Question 8

  

  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?

  • Reach out to the data curators directly before you have started using the trained model to let them know.
  • Use any available data you personally created which is completely original and you can decide what license to use.
  • Only use data explicitly labeled with an open license and ensure the license terms are followed.
  • Reach out to the data curators directly after you have started using the trained model to let them know.

  Reveal Answer Answer: D Next Question

• Question 9

  

  A Generative AI Engineer has a provisioned throughput model serving endpoint as part of a RAGapplication 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?

  • Vector Search
  • Lakeview
  • DBSQL
  • Inference Tables

  Reveal Answer Answer: D Next Question

• Question 10

  

  A team wants to serve a code generation model as an assistant for their software developers. It should support multiple programming languages. Quality is the primary objective.Which of the Databricks Foundation Model APIs, or models available in the Marketplace, would be the best fit?

  • Llama2-70b
  • BGE-large
  • MPT-7b
  • CodeLlama-34B

  Reveal Answer Answer: D Next Question

Page: 1 / 13
Total Questions: 61

Previous Page Next Page