AI-102 Practice Test 2 — 10 Questions

Question 1

You are building an Azure AI Search solution to index a collection of technical manuals. Users need to find documents by searching for specific terms and also have the ability to filter by document category. Which feature should you configure in the index to support filtering?

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

Accepted Answer

Set the 'filterable' property to true on the category field. Setting the 'filterable' property to true on the category field enables Azure AI Search to apply OData filter expressions (e.g., `$filter=category eq 'Networking'`) during query execution. This allows users to narrow search results by document category without requiring the field to be full-text searchable, which is essential for efficient filtering in a technical manuals index.

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Set the 'facetable' property to true on the category field

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Set the 'searchable' property to true on the category field

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Set the 'sortable' property to true on the category field

Question 2

You are building a custom question answering solution using Azure AI Language. Which TWO actions are required to deploy the solution?

Accepted Answer

Create a Custom Question Answering project in Azure AI Language.. A Custom Question Answering project is the container for your question-answer pairs, synonyms, and active learning settings within Azure AI Language. You must create this project to define the knowledge base that the solution will query against.

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Train a custom model using the Azure AI Language training API.

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Create a QnA Maker service in the Azure portal.

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Publish the project to a web app bot.

Question 3

You are reviewing a skillset definition for an Azure AI Search indexer. The indexer is configured to index 1000 PDF documents. After running the indexer, you notice that only 500 documents have sentiment scores. What is the most likely cause?

Accepted Answer

The SplitSkill outputs are not correctly mapped to the SentimentSkill input; the skill runs only on the first page of each document. The SplitSkill divides each PDF into pages, and by default the SentimentSkill runs in the context of each page (e.g., /document/pages/*). If the SplitSkill outputs are not correctly mapped to the SentimentSkill input, the sentiment skill may only process the first page or fail to receive the split content, resulting in sentiment scores for only a subset of documents. Correct mapping ensures that each page's content is passed to the SentimentSkill for analysis.

Answer

The skills are defined in the wrong order; sentiment should run before split

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The SentimentSkill is not supported in this region

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The context of the SentimentSkill should be "/document" instead of "/document/pages/*"

Question 4

Refer to the exhibit. You receive this error when calling an Azure Cognitive Services API. What is the most likely cause?

Accepted Answer

The subscription key is not valid for this Cognitive Services resource.. The error indicates that the subscription key provided is not associated with the Cognitive Services resource being accessed. In Azure Cognitive Services, each resource has a unique set of keys, and using a key from a different resource (even in the same region) will result in a 401 Unauthorized error with this specific message. Option D is correct because the key must match the resource's endpoint exactly.

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The API endpoint is incorrect.

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The subscription key has expired.

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The subscription key is from a different region.

Question 5

You need to summarize a large document using Azure AI Language. Which feature should you use?

Accepted Answer

Document summarization. Document summarization is the correct feature because it is specifically designed to generate concise summaries of large documents, extracting the most important information. Azure AI Language's document summarization uses extractive or abstractive techniques to produce a summary, directly addressing the requirement to summarize a large document.

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Key phrase extraction

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Entity recognition

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Sentiment analysis

Question 6

You are designing an agentic solution that uses Microsoft Copilot Studio and Azure AI Search. The agent needs to answer questions based on confidential documents. Which security measure should you implement to ensure the agent only accesses documents the user has permission to read?

Accepted Answer

Implement document-level security using security filters in the search index.. Azure AI Search supports document-level security through security filters, which allow you to restrict search results based on the user's identity. By storing security identifiers (e.g., group memberships or user IDs) as a field in the index and applying an OData filter at query time, the agent can ensure users only see documents they are permitted to read. This is the standard approach for implementing row-level security in Azure AI Search.

Answer

Disable public network access on the Azure AI Search service.

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Use a managed identity for the agent to access the search index.

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Require multi-factor authentication for all users.

Question 7

Match each Azure Cognitive Search skill to its capability.

Accepted Answer

Entity Recognition: Identifies and categorizes entities in text as people, places, organizations, etc.. Common Azure Cognitive Search skills include Entity Recognition, Key Phrase Extraction, OCR (for image text extraction), and Sentiment Analysis. The correct matches are A and B. Options C and D are mismatched definitions.

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OCR: Detects language and translates text to a target language.

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Sentiment Analysis: Detects the dominant language of a document.

Question 8

Match each Azure AI scenario to the appropriate service.

Accepted Answer

Building a conversational chatbot: Azure Bot Service. Correct matches: Chatbot -> Bot Service, Image moderation -> Computer Vision, Sentiment -> Text Analytics. Common confusions include associating Bot Service with image tasks or mistaking Cognitive Search for text analytics.

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Building a conversational chatbot: Azure Machine Learning

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Analyzing images for content moderation: Azure Bot Service

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Classifying text by sentiment: Azure Cognitive Search

Question 9

You are developing an Azure AI solution that uses pre-built models from Azure AI Vision to analyze images. The solution must be able to detect objects and read printed text. Which TWO capabilities should you use?

Accepted Answer

Object detection. Azure AI Vision's Object Detection capability identifies and locates objects within an image, returning bounding box coordinates and labels. This directly meets the requirement to 'detect objects' in the solution.

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OCR (legacy)

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Facial detection

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Image tagging

Question 10

You need to enforce that only users from your Microsoft Entra ID tenant can call your Azure AI Language API endpoint. Which security mechanism should you configure?

Accepted Answer

Microsoft Entra ID authentication. Microsoft Entra ID authentication (formerly Azure AD) allows you to enforce that only users and applications from your specific Entra ID tenant can call the Azure AI Language API. This is achieved by configuring a managed identity or service principal and assigning it the Cognitive Services User role, which ensures that tokens issued by your tenant are required for access. API keys and IP whitelists do not provide tenant-level identity enforcement, and Azure Firewall is a network-level control that does not authenticate individual users or applications.

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API key authentication

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IP whitelist

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Azure Firewall