AI-102 Practice Test 45 — 15 Questions

Question 1

A company is building a solution to analyze customer reviews images using Azure AI Vision. They need to extract text from images that may contain both printed and handwritten text. Which feature should they use?

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

Accepted Answer

Read API. The Read API is the correct choice because it is specifically designed to extract text from images containing both printed and handwritten text, using advanced OCR capabilities that support mixed content. Unlike the OCR API, which is optimized for printed text only, the Read API leverages deep learning models to handle varied handwriting styles and complex layouts, making it ideal for analyzing customer review images.

Answer

Custom Vision

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OCR API (optical character recognition)

Answer

Azure AI Document Intelligence

Question 2

Your knowledge mining pipeline uses Azure AI Search with a custom skillset that calls an Azure Function. The function sometimes times out for large documents. What is the best way to handle this?

Accepted Answer

Increase the function timeout and ensure the function is in the same region as the search service. Increasing the function timeout (up to the Azure Functions maximum of 10 minutes for the Consumption plan or 30 minutes for the Premium plan) and ensuring the function is in the same region as the search service reduces latency and network overhead, directly addressing timeout issues for large documents. Azure AI Search custom skills must complete within the function's configured timeout, and regional colocation minimizes cross-region data transfer delays.

Answer

Use Azure AI Document Intelligence instead of a custom skill

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Set the function timeout to the maximum of 24 hours

Answer

Move the custom skill to Azure AI Language custom entity recognition

Question 3

You are developing a solution to detect defects on a manufacturing assembly line using computer vision. The solution must classify images as 'defective' or 'non-defective'. You have a limited set of labeled images (500 per class). Which approach should you recommend?

Accepted Answer

Use Azure AI Custom Vision with image classification. Azure AI Custom Vision with image classification is the best choice because it allows you to fine-tune a pre-trained deep learning model on your limited dataset (500 images per class) to classify images as 'defective' or 'non-defective'. This approach requires minimal data and expertise compared to training from scratch, and it is specifically designed for custom classification tasks with small datasets.

Answer

Use Azure AI Vision Image Analysis with a pre-built model

Answer

Use Azure AI Custom Vision with object detection

Answer

Train a deep learning model from scratch using Azure Machine Learning

Question 4

Your team is building a custom question-answering solution using Azure AI Language. The solution must be able to answer questions based on a set of PDF documents. You need to import the documents and create a knowledge base. What should you do first?

Accepted Answer

Use the Azure AI Language service with the custom question answering feature and import the documents. The custom question answering feature of Azure AI Language is specifically designed to ingest documents (including PDFs) and build a knowledge base that can be used for question-answering. This feature provides a built-in pipeline to extract question-answer pairs from documents, create a knowledge base, and deploy it as a service without needing additional search indexing or bot orchestration.

Answer

Use Azure AI Foundry to create a project and upload the documents

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Create an index in Azure AI Search and upload the documents

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Deploy an Azure AI Bot Service and connect it to the documents

Question 5

You are designing an agent using Microsoft Copilot Studio that must handle sensitive employee data such as salaries and performance reviews. The agent should only allow HR managers to access these topics. The solution must comply with data privacy regulations. Which two actions should you take? (Select two.)

Accepted Answer

Configure authentication in Copilot Studio to require Microsoft Entra ID sign-in.. Microsoft Entra ID (formerly Azure AD) authentication is required to enforce role-based access control in Copilot Studio. Without Entra ID, the agent cannot verify the identity of the user or check group membership, which is essential for restricting sensitive topics like salaries and performance reviews to HR managers only.

Answer

Set bot-level authentication to require a specific role.

Answer

Enable detailed audit logging in Microsoft Purview.

Answer

Apply data loss prevention policies in Microsoft Purview.

Question 6

You see the exhibit from an Azure OpenAI chat completion request. The assistant is not calling the get_weather function when asked about the weather. What is the most likely reason?

Accepted Answer

The function is defined in the system message but not in the 'tools' array. D is correct because in Azure OpenAI, functions must be defined in the 'tools' array of the chat completion request to be available for the model to call. Defining a function only in the system message does not register it as a callable tool; the model can see the description but cannot invoke it. Without the function in 'tools', the assistant will ignore the request to call get_weather.

Answer

The required parameter 'location' is missing from the user message

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Function calling is not supported in the current Azure OpenAI version

Answer

The function definition is malformed

Question 7

Refer to the exhibit. You are calling the Azure AI Language API for conversational language understanding (CLU). The CLU project 'SupportBot' has an intent 'CancelOrder' with an entity 'OrderNumber' of type 'Number'. The deployment 'production' is active. What is the expected output?

Accepted Answer

The response will contain the top intent 'CancelOrder' and the entity 'OrderNumber' with value '12345'.. D is correct because the CLU project 'SupportBot' has a defined intent 'CancelOrder' with an entity 'OrderNumber' of type 'Number'. The 'Number' entity type in Azure AI Language automatically extracts numeric values from the utterance, stripping non-numeric characters like the hash (#). Since the deployment is active, the response returns the top intent and the entity with the numeric value '12345'.

Answer

The response will contain an error because the deployment is not active.

Answer

The response will contain the entity 'OrderNumber' with value '#12345' because the hash is part of the entity.

Answer

The response will contain only the top intent, but no entities because the entity type is not recognized.

Question 8

Which THREE actions should an engineer take when deploying a custom question answering project in Azure Cognitive Service for Language?

Accepted Answer

Set up a multi-turn extraction policy for follow-up questions.. Multi-turn extraction is a core feature of custom question answering that allows the system to handle follow-up questions by maintaining context across turns. This is essential for conversational flows where a user's subsequent query depends on the previous answer, and it is configured via the project settings in Language Studio.

Answer

Integrate LUIS for intent detection.

Answer

Configure a single-turn extraction policy.

Question 9

Your team develops a document translation solution using Azure AI Translator. The solution must translate documents while preserving formatting and layout. Which feature should you use?

Accepted Answer

Azure AI Translator Document Translation. Azure AI Translator Document Translation is specifically designed to translate entire documents while preserving the original formatting, structure, and layout. Unlike Text Translation, which handles only plain text strings, Document Translation processes files (e.g., PDF, Word, Excel) and returns a translated version with the same formatting, making it the correct choice for this requirement.

Answer

Azure AI Translator Custom Translator

Answer

Azure AI Document Intelligence

Answer

Azure AI Translator Text Translation

Question 10

You are designing a knowledge mining solution for a large legal firm. The solution must extract key clauses, parties, and dates from thousands of PDF contracts. You need to minimize manual labeling effort while achieving high extraction accuracy. Which Azure AI service should you use?

Accepted Answer

Azure AI Document Intelligence custom extraction model. Azure AI Document Intelligence custom extraction model is the correct choice because it is specifically designed to extract structured fields (like clauses, parties, and dates) from documents such as PDF contracts. It uses a prebuilt layout model combined with custom training on a small set of labeled documents, minimizing manual labeling effort while achieving high accuracy through transfer learning and table/key-value pair extraction.

Answer

Azure OpenAI Service with GPT-4 prompt engineering

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Azure AI Search with built-in blob indexing

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Azure AI Language custom named entity recognition

Question 11

Refer to the exhibit. You are configuring content filtering for an Azure OpenAI deployment using a JSON policy. You want to block all content with a 'Hate' severity of 'medium' or higher. What should you modify in the policy?

Accepted Answer

Modify the "severityThreshold" for "Hate" to "medium".. In Azure OpenAI content filtering, the 'severityThreshold' for a given category (like 'Hate') defines the minimum severity level at which content is filtered. Setting it to 'medium' means all content with a severity of 'medium' or higher (including 'high') will be blocked, which matches the requirement to block 'Hate' severity 'medium' or higher.

Answer

Change the "severityThreshold" for "SelfHarm" to "low".

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Change the "contentTypes" to include only "Normal".

Answer

Add a "policyAction" with "block" to the "BlockHateSpeech" policy.

Question 12

A research lab wants to use Azure OpenAI to generate synthetic data for training a model. They need to generate a large volume of data quickly and cost-effectively. Which approach should they use?

Accepted Answer

Use the batch API to process requests asynchronously.. The batch API is designed for high-throughput, asynchronous processing of large volumes of requests, making it ideal for generating synthetic data at scale. It allows the lab to submit many prompts in a single batch, which Azure OpenAI processes efficiently, reducing both cost and time compared to real-time processing.

Answer

Fine-tune a model to generate the data locally.

Answer

Use the streaming API with multiple concurrent connections.

Answer

Deploy a model on Azure Functions and call it in parallel.

Question 13

You are using Microsoft Copilot Studio to create an agent that handles customer support. The agent needs to understand the user's intent from free-text input. Which feature should you use to map user utterances to specific topics?

Accepted Answer

Define trigger phrases for each topic. In Microsoft Copilot Studio, trigger phrases are the primary mechanism for mapping user utterances to specific topics. When a user types a free-text input, the agent's natural language understanding (NLU) engine compares the input against the defined trigger phrases for each topic. The topic with the highest confidence score based on semantic similarity is triggered, enabling intent recognition without requiring exact keyword matches.

Answer

Configure variables to capture user input

Answer

Add actions to process the input

Answer

Create custom entities to extract key phrases

Question 14

You are building a conversational AI solution that must handle multiple intents in a single user utterance. Which Azure AI feature should you use?

Accepted Answer

Use the orchestration workflow feature in Conversational Language Understanding.. The orchestration workflow feature in Conversational Language Understanding (CLU) is designed to handle multiple intents within a single user utterance by connecting to different projects (e.g., CLU, QnA Maker, or custom question answering) and routing the utterance to the appropriate service. This allows the solution to parse complex utterances that may trigger multiple intents across different domains, which is exactly what the scenario requires.

Answer

Use QnA Maker with multiple QnA pairs.

Answer

Use a single Conversational Language Understanding project with multiple intents.

Answer

Use Azure Bot Service with multiple dialogs.

Question 15

A developer is using Azure OpenAI to generate code snippets. The developer needs to ensure that the generated code does not contain security vulnerabilities. Which TWO actions should the developer take? (Choose two.)

Accepted Answer

Include examples of secure coding practices in the prompt.. Including examples of secure coding practices in the prompt (few-shot prompting) directly guides the model to follow those patterns, reducing insecure code generation. Option D is also correct because Azure OpenAI's content filtering feature can be configured to block code patterns that match known vulnerabilities (e.g., SQL injection, buffer overflows), providing an additional safety layer. Options B (high max_tokens), C (fine-tuning on insecure code), and E (system message) are not effective or counterproductive.

Answer

Set the max_tokens parameter to a high value to allow longer outputs.

Answer

Fine-tune the model on a dataset containing examples of insecure code.

Answer

Add a system message that instructs the model to never generate insecure code.