AB-731 practice questions 1–10

1. Question 1 · 45 in bank

   Your company plans to build a generative AI solution based on internal data. You recommend using Microsoft Foundry as a starting point to develop and manage the solution. What is a key benefit of using Microsoft Foundry for this project?

   • AProvides a scalable platform for developing and deploying generative AI solutions.
   • BRemoves the need to select or configure the underlying AI model.
   • CEnables business users to build generative AI solutions.
   • DOffers a low-code platform for developing generative AI solutions.

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   Answer: A

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2. Question 2 · 45 in bank

   Which business requirement most closely relates to grounding a generative AI model?

   • Asupporting multiple languages
   • Bmeasuring the number of user interactions per day
   • Cenabling users to interact by using natural language queries
   • Densuring that verified company data sources are used for response generation

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   Answer: D

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3. Question 3 · 45 in bank

   You need to create a custom Azure Machine Learning model. The data used to train the model is consistent and uniform. What should you do first?

   • APrepare the training data.
   • BEvaluate the model.
   • CTrain the model.
   • DTune hyperparameters.
   • EDeploy the model.

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   Answer: A

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4. Question 4 · 45 in bank

   Your company uses a non-reasoning generative AI model to create textual content. You discover that the model’s responses are inconsistent and do NOT meet expectations. You need to improve the prompts. What should you do? More than one answer choice may achieve the goal. Select the BEST answer.

   • AProvide the prompts with extensive examples of the expected output.
   • BAdd the context, sources, and expectations to the prompts.
   • CUse technical terms in the prompts to enhance AI comprehension.
   • DAdd only a single concise requirement to the prompts.

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   Answer: B

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5. Question 5 · 45 in bank

   Your company plans to use generative AI to help project managers and engineers work with construction blueprints stored as PDF files. You need to recommend a generative AI solution that meets the following business requirements: Processes both images and text - Summarizes the design of a building Answers user questions about a building’s design Extracts information from blueprints, such as the location of electrical, heating, and plumbing systems What should you recommend?

   • Aa multi-modal solution
   • Ban optical character recognition (OCR) solution
   • Ca text completion solution
   • Da document summarization solution

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   Answer: A

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6. Question 6 · 45 in bank

   In which scenario is Azure Machine Learning most likely to deliver strategic value for an organization?

   • AUsing historical sales data to forecast demand across product categories.
   • BDigitizing a paper-based process to reduce errors.
   • CEntering customer feedback into a spreadsheet to understand sentiment.
   • DSending personalized emails to customers based on the customer location.

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   Answer: A

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7. Question 7 · 45 in bank

   Your company uses a generative AI solution. You need to improve the quality of responses by using grounding. Which statement accurately describes how grounding improves accuracy and relevancy?

   • Areferences a diverse set of people, disciplines, and perspectives
   • Bexplains how and why AI models generate content
   • Canchors the responses in specific data sources
   • Dspecifies the strengths and weaknesses of the AI model

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   Answer: C

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8. Question 8 · 45 in bank

   You plan to meet with a group of stakeholders to discuss how generative AI can benefit your company. You need to provide the stakeholders with a relevant description of generative AI during the meeting. Which description should you use?

   • AGenerative AI is designed to generate responses based on a user’s natural language prompts.
   • BGenerative AI is designed to translate documents into other languages.
   • CGenerative AI is designed to predict future trends based on historical data.
   • DGenerative AI is designed to recommend products based on user behavior.

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   Answer: A

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9. Question 9 · 45 in bank

   Which statement accurately describes the difference between a pretrained generative AI model and a fine-tuned generative AI model?

   • AA pretrained model requires labeled data, while a fine-tuned model does not.
   • BA pretrained model is faster to train than a fine-tuned model because the pretrained model uses fewer parameters.
   • CA pretrained model is trained on broad datasets, while a fine-tuned model is adapted to perform well on a narrower, domain-specific dataset.
   • DA pretrained model is optimized for a specific task, while a fine-tuned model is designed for general-purpose use.

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   Answer: C

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10. Question 10 · 45 in bank

    Your company creates a custom Azure Machine Learning model that uses a generative AI assistant. The model initially delivers strong results. However, six months later, the model predictions become noticeably less accurate. What is a possible cause of the issue?

    • AThe model requires additional compute resources.
    • BThe input data changed over time.
    • CThe model was trained incorrectly.

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    Answer: B

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AB-731 practice, question 1. 45 questions available.