AI-102 Practice Test 49 — 15 Questions

Question 1

A healthcare organization uses Azure AI Health Insights to extract medical insights from unstructured clinical notes. The solution must comply with HIPAA. Which configuration is required?

Accepted Answer

Configure the Azure AI services resource to use a private endpoint and disable public network access. HIPAA compliance for Azure AI Health Insights requires network isolation to prevent unauthorized access to protected health information (PHI). A private endpoint assigns the Azure AI services resource a private IP address within the customer's virtual network, and disabling public network access ensures all traffic stays within the Microsoft backbone, eliminating exposure to the public internet. This configuration meets the HIPAA Security Rule's requirement for technical safeguards, specifically access control and transmission security.

Answer

Store the clinical notes in Azure Storage with Azure AD authentication only

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Enable public network access but use a firewall rule to restrict IP addresses

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Use a system-assigned managed identity for authentication

Question 2

You are planning to use Azure AI Document Intelligence to process a large volume of mixed document types (invoices, receipts, and purchase orders). The solution must automatically classify each document type and extract relevant fields. What should you configure?

Accepted Answer

Create a custom classification model to identify document types, then use extraction models. Azure AI Document Intelligence (formerly Form Recognizer) requires a two-step process for mixed document types: first, a custom classification model identifies each document type (invoice, receipt, purchase order), then separate extraction models (custom or prebuilt) extract the relevant fields from each classified type. This approach ensures accurate routing and field extraction without relying on filenames or brittle regex patterns.

Answer

Use the Form Recognizer service with neural models

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Use prebuilt models for each document type and route based on filename

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Use the Read model to extract all text and then use regular expressions to classify

Question 3

Which TWO Azure AI services can be used to perform optical character recognition (OCR) on images? (Choose two.)

Accepted Answer

Azure AI Document Intelligence Read model. Azure AI Document Intelligence Read model (option A) is correct because it is specifically designed to extract printed and handwritten text from images and documents using OCR. It leverages deep learning models to analyze text layout, including lines and words, and is optimized for document-centric OCR tasks.

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Azure Video Indexer

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Azure AI Custom Vision

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Azure AI Face API

Question 4

A healthcare organization uses Azure AI Health Insights to extract medical insights from unstructured clinical notes. The solution must comply with HIPAA. Which configuration is required?

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

Accepted Answer

Text Analytics for health. Text Analytics for health is a specialized Azure AI Language feature designed to extract and label medical entities from unstructured clinical text, such as diagnoses, medications, and procedures. It also includes a built-in PHI detection and redaction capability that automatically identifies and masks protected health information, enabling HIPAA compliance without requiring custom model training.

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Azure Purview Information Protection

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Custom named entity recognition (NER)

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Azure AI Document Intelligence

Question 5

A company uses Azure AI Language to analyze customer reviews. They need to detect sentiment, extract key phrases, and identify named entities. Which THREE capabilities should they combine?

Accepted Answer

Named entity recognition (NER). Named entity recognition (NER) is correct because it identifies and categorizes named entities (e.g., people, organizations, locations) in text, which is essential for extracting structured information from customer reviews. Combined with sentiment analysis and key phrase extraction, NER enables a comprehensive understanding of customer feedback by detecting sentiment, surfacing important terms, and recognizing specific entities mentioned.

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Abstractive summarization

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Language detection

Question 6

A company wants to integrate their Copilot Studio agent with an on-premises ERP system using an API. The on-premises API requires Windows Authentication. The agent must call the API securely without exposing credentials. Which Azure service should be used to enable this integration?

Accepted Answer

Azure API Management with on-premises data gateway.. Azure API Management with an on-premises data gateway enables secure integration with on-premises APIs that require Windows Authentication. The gateway acts as a bridge, allowing the Copilot Studio agent to call the on-premises ERP API without exposing credentials, as the gateway handles authentication and secure connectivity via Azure Relay.

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Azure Functions with HTTP trigger.

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Azure VPN Gateway to connect to the on-premises network.

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Azure Logic Apps with a connector.

Question 7

You are building a customer support chatbot using Azure OpenAI Service. The chatbot must only answer questions related to the company's products and policies. It should refuse to answer off-topic questions. You need to implement this restriction effectively. What should you do?

Accepted Answer

Implement Retrieval Augmented Generation (RAG) with your product and policy data. Retrieval Augmented Generation (RAG) grounds the model's responses in your specific product and policy data by retrieving relevant documents from a vector database (e.g., Azure Cognitive Search) and injecting them into the prompt. This ensures the chatbot can only answer questions that have matching context in your data, and it naturally refuses off-topic queries because no relevant documents are retrieved, allowing the system to return a default refusal message. RAG provides a dynamic, data-driven boundary without modifying the underlying model.

Answer

Fine-tune the model on a dataset of product-related conversations

Answer

Use a system message that instructs the model to stay on topic

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Set the temperature parameter to 0 to reduce randomness

Question 8

You have the above indexer configuration. The indexer processes a batch of 10 documents. In that batch, 3 documents fail. What happens?

Accepted Answer

The indexer fails the entire batch but continues with the next batch.. Azure AI Search indexers use a batch-level failure policy: if the number of failed documents in a batch exceeds the configured 'maxFailedItems' threshold (default 0), the entire batch is marked as failed and skipped, but the indexer continues processing subsequent batches. This behavior is controlled by the indexer's 'maxFailedItems' and 'maxFailedItemsPerBatch' properties, which default to 0, meaning any failure in a batch causes the batch to be skipped while the indexer moves on.

Answer

The indexer skips the failed documents and continues with the same batch.

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The indexer stops completely because 3 documents failed.

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The indexer retries the failed documents.

Question 9

Which TWO monitoring metrics should you track to ensure the health and performance of an Azure AI Search service used for a customer-facing product catalog?

Accepted Answer

Throttled search queries count.. Throttled search queries count (Option A) is a critical health metric because it directly indicates when the search service is under excessive load, causing requests to be rate-limited. For a customer-facing product catalog, throttling degrades user experience and can lead to failed searches. Tracking this metric helps you decide when to scale up replicas or partitions to maintain service level agreements.

Answer

Indexer execution history and duration.

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Storage used in GB.

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Number of successful search requests.

Question 10

You are developing a generative AI solution that uses Azure OpenAI Service. The solution must generate product descriptions in multiple languages. You need to ensure that the model consistently follows specific formatting rules, such as including a bullet list of features. Which strategy should you use?

Accepted Answer

Set a system message with explicit formatting instructions.. System messages in Azure OpenAI Service allow you to set persistent instructions that guide the model's behavior across the entire conversation. By including explicit formatting rules—such as requiring a bullet list of features—in the system message, you enforce consistent output structure without retraining the model. This approach is efficient, cost-effective, and directly leverages the API's design for controlling response format.

Answer

Fine-tune the model with a dataset containing formatted examples.

Answer

Increase the max_tokens parameter to allow longer outputs.

Answer

Adjust the temperature parameter to a lower value.

Question 11

Refer to the exhibit. You called the Key Phrase Extraction API on two documents. What is the total number of key phrases extracted?

Accepted Answer

5. The Key Phrase Extraction API returns a list of key phrases per document. In this case, Document 1 returns 'weather', 'Seattle', and 'rainy', while Document 2 returns 'weather' and 'Seattle'. The total number of unique key phrases across both documents is 3 ('weather', 'Seattle', 'rainy'), but the question asks for the total number of key phrases extracted, which counts each occurrence per document. That gives 3 + 2 = 5 key phrases. Option B is correct because the API outputs phrases per document, not deduplicated globally.

Answer

7

Answer

3

Answer

2

Question 12

Match each Azure Bot Service channel to its description.

Accepted Answer

Direct Line: Enables communication between your bot and your own client application.. The correct matches are: Direct Line for custom client communication, Web Chat for embeddable chat, Microsoft Teams for team collaboration, and Facebook Messenger for Messenger integration. Common mistakes include confusing Direct Line and Web Chat definitions.

Answer

Direct Line: Embeds a chat control in a web page.

Answer

Microsoft Teams: Enables communication between your bot and your own client application.

Question 13

A company uses Azure Cognitive Search to index customer support emails. They need to implement a custom skill that extracts the sentiment of the email body and also identifies the primary product mentioned. The custom skill is a Python function deployed as an Azure Function. They want to ensure the skill can process multiple documents concurrently and handle errors gracefully. Which THREE configurations should they apply?

Accepted Answer

Set the inputs of the skill to include the 'text' field from the enriched document and the 'product' field from a previous skill.. The custom skill must receive the email body text for sentiment analysis and the product field from a prior skill (e.g., a key phrase extraction or entity recognition skill) to identify the primary product. This ensures the Azure Function has all required inputs to produce the desired outputs (sentiment score and product name).

Answer

Set continueOnError to false to ensure that if the skill fails for one document, the entire indexer run stops.

Answer

Set the context property to '/document/pages/*' to process each page of the email individually.

Question 14

A developer is creating a custom question answering project in Azure AI Language. The knowledge base contains product manuals in PDF format. Which step is essential before importing the PDFs?

Accepted Answer

Ensure PDFs are in a supported format and accessible. Before importing PDFs into a custom question answering project in Azure AI Language, the essential step is to ensure the PDFs are in a supported format (e.g., searchable PDF, not scanned images without OCR) and accessible via a valid URL or local path. This is because the import process relies on the service being able to read and extract text from the documents; unsupported or inaccessible files will cause the import to fail.

Answer

Create an Azure AI Search index

Answer

Deploy a QnA Maker service

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Translate PDFs to English

Question 15

You need to choose Azure services to build a computer vision pipeline that ingests images from multiple sources, extracts text using OCR, and stores extracted metadata in a Cosmos DB database. Which TWO services should you use?

Accepted Answer

Azure AI Vision. Azure AI Vision (option A) provides the OCR capability needed to extract text from images via its Read API, which is the core requirement of the pipeline. Azure Functions (option C) is the correct compute service to orchestrate the ingestion, call the OCR API, and write the extracted metadata to Cosmos DB, as it supports event-driven triggers and can scale with image volume. Together, they form a serverless pipeline that meets the stated requirements.

Answer

Azure Cognitive Search

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Azure Logic Apps

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Azure Blob Storage