AI-102 Practice Test 8 — 10 Questions

Question 1

Your organization uses Microsoft Syntex to automatically classify and extract metadata from documents stored in SharePoint. You need to extend this capability to also extract entities such as invoice numbers and dates from PDF invoices that are uploaded to SharePoint. What should you do?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Create a document understanding model in Syntex that extracts entities from invoices.. Microsoft Syntex document understanding models can classify documents and extract entities such as invoice numbers and dates. Option A is incorrect because Syntex does not use AI Builder's out-of-the-box entity extraction; it uses its own model training. Option B is incorrect because Azure AI Search is a search service, not an entity extraction service integrated with Syntex. Option C is incorrect because Power Automate with AI Builder is a separate workflow automation approach, not part of Syntex. Therefore, option D is correct: create a document understanding model in Syntex that extracts entities from invoices.

Answer

Create a custom entity extraction model in Syntex using AI Builder.

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Integrate Azure AI Search with SharePoint to extract entities.

Answer

Use Power Automate with AI Builder to extract entities from invoices.

Question 2

Refer to the exhibit. You are using Microsoft Graph to retrieve user information for use in a Microsoft 365 Copilot extension. The response shows that the mail and mobilePhone fields are null. What is the most likely reason?

Accepted Answer

The user has not configured those properties in their Microsoft Entra ID profile.. The mail and mobilePhone fields are null because the user has not populated these attributes in their Microsoft Entra ID (formerly Azure AD) profile. Microsoft Graph returns the actual stored values for these properties; if they are empty or unset, the API response will show null. This is the most common and straightforward reason for null values in user profile fields.

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The API call required additional permissions.

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The user is a guest user.

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The user does not exist in the tenant.

Question 3

You need to provision an Azure AI Language resource that supports custom text classification. Which pricing tier should you select to use the custom training feature?

Accepted Answer

Standard (S). The Standard (S) tier is the only pricing tier for Azure AI Language that supports custom text classification, including the custom training feature. The Free (F0) tier is limited to pre-built capabilities and cannot be used for training custom models, while Basic (B) and Premium (P) tiers do not exist for this service.

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Free (F0)

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Basic (B)

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Premium (P)

Question 4

You are using Azure AI Document Intelligence to extract data from scanned contracts. The contracts contain tables and handwritten signatures. Which TWO features should you enable?

Accepted Answer

Train a custom neural model to recognize handwritten signatures.. Options A and B are correct because a custom neural model can be trained to recognize handwritten signatures (A), and enabling table extraction in the custom model extracts tables from contracts (B). Option C is incorrect because OCR is already enabled by default in Document Intelligence and does not need to be separately enabled. Option D is wrong because form recognition for key-value pairs is not required for this scenario, as the focus is on tables and signatures. Option E is wrong because the prebuilt-layout model does not support custom training for signature recognition and may not handle handwritten elements as accurately as a custom model.

Answer

Enable OCR to read scanned text.

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Use form recognition to capture key-value pairs.

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Use the prebuilt-layout model for all extraction.

Question 5

Refer to the exhibit. You are deploying an agent in Microsoft Foundry using the ARM template snippet above. The agent needs to call Microsoft Graph API to reset a user's password. However, the deployment fails with an authorization error. What is the most likely cause?

Accepted Answer

The managed identity does not have the 'User.ReadWrite.All' delegated permission for Microsoft Graph.. The agent uses a managed identity to authenticate to Microsoft Graph, and the error indicates an authorization failure. For the agent to call Graph API to reset a user's password, the managed identity must be granted the 'User.ReadWrite.All' application permission (not delegated) via an API permission assignment in Azure AD. Without this permission, the Graph API returns a 403 Forbidden error, even if the endpoint and ARM template syntax are correct.

Answer

The Graph API endpoint URL is incorrect.

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The apiVersion '2025-01-01-preview' is not supported for agent deployments.

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The resourceId for managed identity is missing the 'Microsoft.ManagedIdentity/userAssignedIdentities' resource type.

Question 6

A company is using Azure Cognitive Service for Language to analyze customer support transcripts. They want to identify custom categories (e.g., 'billing', 'technical support') using a custom text classification model. After training and deploying the model, they receive many false positives for the 'billing' category. What is the best first step to improve model accuracy?

Accepted Answer

Review the training data for the 'billing' category and correct any mislabeled examples.. False positives for a specific category like 'billing' most often stem from mislabeled or ambiguous training examples in that category. By reviewing and correcting the training data for 'billing', you directly address the root cause of the model's confusion, which is the most effective first step in custom text classification model improvement.

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Add more training data to all categories to improve overall model performance.

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Use a different Azure AI service, such as key phrase extraction, to identify billing-related content.

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Increase the confidence threshold for the 'billing' category to reduce false positives.

Question 7

You are responsible for an Azure AI solution that uses Custom Vision to classify manufacturing defects. The model must achieve high recall to avoid missing defects. The current model has high precision but low recall. Which action should you take?

Accepted Answer

Lower the probability threshold for the defect class. Lowering the probability threshold for the defect class means the model will classify an image as defective even when its confidence score is lower. This increases the number of true positives (defects caught), directly improving recall at the cost of potentially more false positives. In Custom Vision, the default probability threshold is 50%, and adjusting it downward is the standard technique to prioritize recall over precision.

Answer

Add more images of non-defective items to the training set

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Increase the number of training iterations

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Increase the probability threshold for the defect class

Question 8

A company is building a chatbot using Azure AI Language. The chatbot must understand user intents and extract entities like dates and locations. The solution should minimize manual labeling effort. Which feature should the team use?

Accepted Answer

CLU prebuilt entity components. CLU prebuilt entity components provide ready-made entity extraction for common types like dates and locations without requiring manual labeling. This minimizes manual effort while still allowing the chatbot to understand user intents and extract entities, as the prebuilt components are domain-agnostic and cover a wide range of entity types out of the box.

Answer

Conversational Language Understanding (CLU) Orchestration Workflow

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CLU prebuilt intents

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Azure AI QnA Maker

Question 9

Which TWO Azure AI services can be used to detect objects in images?

Accepted Answer

Custom Vision. Custom Vision (Option C) is correct because it allows you to train a custom image classification or object detection model using your own labeled images. You can upload images, tag objects with bounding boxes, and then use the trained model to detect specific objects in new images, making it a valid choice for object detection tasks.

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Video Indexer

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Face API

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Azure AI Document Intelligence

Question 10

Which TWO Azure AI services can be used to build a conversational chatbot that uses generative AI? (Choose two.)

Accepted Answer

Azure AI Bot Service. Azure AI Bot Service (B) provides a dedicated platform for building, deploying, and managing conversational chatbots, integrating with channels like Microsoft Teams and Slack. Azure OpenAI Service (E) enables generative AI capabilities by providing access to large language models (e.g., GPT-4) that can generate human-like responses, making it ideal for powering the conversational intelligence of a chatbot.

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Azure AI Search

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Azure AI Translator

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Azure AI Language