AI-102 Plan and manage an Azure AI solution Practice Test 12 — 15 Questions

Question 1

You are designing an AI solution that uses Azure AI Document Intelligence to extract data from invoices. The solution must handle a high volume of documents with varying layouts. Which approach should you use?

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

Accepted Answer

Train a custom neural model with labeled invoices. Custom neural models in Azure AI Document Intelligence are designed to handle high volumes of documents with varying layouts. Unlike fixed template models, neural models learn from labeled examples and generalize across different invoice structures, making them ideal for diverse, high-volume scenarios.

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Use a custom template model with fixed field positions

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Use the prebuilt invoice model

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Extract text using OCR and then use regex parsing

Question 2

Your team is developing a chatbot using Azure AI Bot Service with Language Understanding (LUIS). You need to improve intent recognition for user queries that contain typos. What should you recommend?

Accepted Answer

Enable Bing Spell Check in the LUIS app settings. Enabling Bing Spell Check in the LUIS app settings allows the service to automatically correct typos in user utterances before they are processed for intent recognition. This built-in feature integrates directly with LUIS at the endpoint, correcting misspelled words to improve the accuracy of intent and entity extraction without requiring manual data augmentation or external services.

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Add synonym lists for common misspellings

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Use Azure Cognitive Search to correct typos

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Train the model with many examples containing typos

Question 3

You are planning to deploy an Azure AI Content Safety solution. What is the primary requirement for using the service?

Accepted Answer

An active Azure subscription. An active Azure subscription is the primary requirement because Azure AI Content Safety is a cloud-based service that requires a valid subscription for resource provisioning, API access, and billing. Without an Azure subscription, you cannot create the Content Safety resource or authenticate API calls, regardless of other configurations.

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Data must be stored in the same region as the service

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All users must have Microsoft Entra ID P2 licenses

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The application must be written in C#

Question 4

Your organization uses Microsoft Purview to govern AI models. You need to ensure that data used for training complies with internal policies. What should you configure?

Accepted Answer

Set up Data Estate Insights to monitor data usage. Data Estate Insights in Microsoft Purview provides monitoring and analytics over data estate health, including data usage patterns. By configuring Data Estate Insights, you can track how training data is accessed and used, enabling you to verify compliance with internal policies on data consumption for AI model training.

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Use Microsoft Purview Data Map to catalog training data

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Apply sensitivity labels to training data

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Enable Microsoft Purview Information Protection

Question 5

You are designing a solution that uses Azure AI Translator to translate customer support tickets. The solution must handle confidential data and ensure no data leaves the specified Azure region. What should you do?

Accepted Answer

Create a Translator resource with a private endpoint and disable public network access. Using a private endpoint ensures that all traffic to the Translator resource stays within the Azure virtual network and never traverses the public internet, while disabling public network access enforces that no data can leave the specified Azure region. This combination meets the requirement for handling confidential data with regional data residency guarantees.

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Enable customer-managed keys and disable logging

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Use the global Translator endpoint

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Use the S1 pricing tier to ensure regional processing

Question 6

You need to monitor the performance of an Azure AI Language service custom entity recognition model. Which metric should you track to evaluate the model's ability to correctly identify entities?

Accepted Answer

F1 score. The F1 score is the standard metric for evaluating custom entity recognition models in Azure AI Language, as it balances precision (correctly identified entities) and recall (missed entities). Unlike accuracy, which can be misleading due to class imbalance in entity labeling, F1 provides a harmonic mean that reflects the model's ability to correctly identify entities without bias toward the majority class.

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Throughput

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Response latency

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Accuracy

Question 7

Which TWO actions should you take when designing an Azure AI solution that uses Microsoft Foundry to ensure responsible AI practices?

Accepted Answer

Implement a human-in-the-loop review for critical decisions. Implementing a human-in-the-loop review provides oversight for critical decisions. Option C is correct because running an AI fairness assessment detects bias. Option B is wrong because optimizing for maximum throughput is about performance, not responsible AI. Option D is wrong because storing all training data indefinitely may violate privacy and is not a recommended practice for responsible AI. Option E is wrong because removing all explainability metrics hinders transparency, which is important for responsible AI.

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Optimize the model for maximum throughput

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Store all training data indefinitely for auditability

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Remove all explainability metrics to simplify the model

Question 8

Which THREE considerations are important when planning to use Azure OpenAI Service in a production environment?

Accepted Answer

Configure content filtering to block harmful outputs. Azure OpenAI Service includes built-in content filtering to detect and block harmful outputs such as hate, violence, or self-harm. This is a critical safety and compliance requirement for production deployments, as it helps meet responsible AI principles and regulatory obligations. Without configuring content filters, the service could generate inappropriate responses that violate usage policies or legal standards.

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Train a custom model from scratch using your own data

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Deploy the service within a virtual network (VNet)

Question 9

Which TWO Azure AI services can be used together to build a solution that transcribes customer service calls and detects sentiment?

Accepted Answer

Azure AI Language (sentiment analysis). Azure AI Speech's speech-to-text capability transcribes the audio of customer service calls into text, while Azure AI Language's sentiment analysis evaluates that text to determine the overall sentiment (e.g., positive, negative, or neutral). Together, they form a complete pipeline for analyzing call recordings. Option A is correct because sentiment analysis is the specific feature within Azure AI Language that detects sentiment from text. Option B is correct because speech-to-text is the specific feature within Azure AI Speech that converts audio to text.

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Azure AI Translator

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Azure AI Speech (text-to-speech)

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Azure AI Language (conversational language understanding)

Question 10

Refer to the exhibit. You are reviewing an Azure OpenAI Service API request. The deployment-id is 'gpt-4o'. The user asks 'What is the capital of France?' The response is cut off mid-sentence. Based on the parameters, what is the most likely cause?

Accepted Answer

The stop parameter is causing early termination. The `stop` parameter in an Azure OpenAI API request defines a sequence of tokens that, when generated, causes the model to stop producing further output. If the `stop` sequence appears in the generated text, the response will be truncated at that point, even mid-sentence. In this scenario, the cut-off response is most likely due to the `stop` parameter matching a token in the generated output, not because of token limits or temperature settings.

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The max_tokens value is too low

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The temperature setting is too high

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The system message is missing a context

Question 11

Refer to the exhibit. You are creating a Custom Vision project using the Azure AI Custom Vision API. The training data is stored in Azure Blob Storage with a SAS URI. The project creation fails with an authorization error. What is the most likely reason?

Accepted Answer

The SAS token is expired or has insufficient permissions. The Custom Vision project creation fails because the SAS URI used to access training data in Azure Blob Storage has an expired token or lacks sufficient permissions (e.g., read/list). Custom Vision requires a valid SAS token with at least read and list permissions to import images from the container. An expired or under-permissioned SAS token results in an authorization error when the service attempts to access the blob storage.

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The domain 'general' is invalid

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The exportModelContainerUri is missing

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The project type 'Classification' is not supported

Question 12

You are the AI architect for a global e-commerce company. The company uses Azure AI services to power its product recommendation engine. The current solution uses Azure AI Language to extract product attributes from descriptions and Azure AI Search to index and retrieve products. The company is expanding to new markets and must comply with data residency regulations in the European Union and Asia. Additionally, the solution must handle a 10x increase in traffic during holiday sales without downtime. You need to design a solution that meets these requirements. The solution must use Azure AI Language and Azure AI Search. You have the following options: A) Deploy separate Azure AI Language and Azure AI Search resources in each region (EU and Asia) and use Azure Traffic Manager to route users to the nearest region. Use geo-replication for Azure AI Search. B) Deploy a single Azure AI Language resource in the US and use Azure AI Search with geo-replication to handle traffic. Use Azure Front Door for global routing. C) Deploy Azure AI Language resources in each region and use a global Azure AI Search resource with replication. Use Azure Load Balancer to distribute traffic. D) Deploy Azure AI Language and Azure AI Search resources in the US only, and use Azure CDN to cache responses globally. Which option should you choose?

Accepted Answer

Deploy separate resources in each region with Traffic Manager and geo-replication.. Deploying separate Azure AI Language and Azure AI Search resources in each region (EU and Asia) ensures compliance with data residency regulations by keeping data within regional boundaries. Azure Traffic Manager routes users to the nearest region for low latency, and geo-replication for Azure AI Search provides high availability and disaster recovery, handling the 10x traffic increase during holiday sales without downtime.

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Deploy a single US resource with geo-replication and Front Door.

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Deploy US-only resources with CDN caching.

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Deploy Language in each region with a global Search resource.

Question 13

Your organization is deploying an Azure AI service for document translation. The solution must support custom glossaries and real-time translation. Cost optimization is a key requirement. Which pricing tier should you choose?

Accepted Answer

Standard S1. The Standard S1 tier is the correct choice because it supports custom glossaries and real-time translation, which are required for the document translation solution. Additionally, S1 offers a balance of features and cost, making it optimal for production workloads where cost optimization is a key requirement, unlike the Free F0 tier which has limited throughput and no SLA, or the Premium S2 tier which is designed for high-volume scenarios at a higher cost.

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Free F0

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Basic S0

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Premium S2

Question 14

You are planning an Azure AI solution that processes sensitive customer data. Compliance requires encryption at rest using a customer-managed key (CMK) stored in Azure Key Vault. The AI resource must also be accessible only from specific virtual networks. Which two configurations are necessary? (Choose two.)

Accepted Answer

Enable customer-managed key encryption for the Azure AI service.. This is a multi-select question requiring two correct answers. Option C is correct because enabling customer-managed key encryption for the Azure AI service meets the compliance requirement for encryption at rest with CMK stored in Azure Key Vault. Option E is correct because configuring private endpoints ensures the AI resource is accessible only from specific virtual networks, providing network isolation. Option A is incorrect because a system-assigned managed identity is not required for CMK or network access; it is used for authentication. Option B is incorrect because Azure Firewall inspects outbound traffic, which is not mandated by the requirements. Option D is incorrect because public network access must be disabled when using private endpoints; allowing selected IP addresses does not achieve the required virtual network restriction.

Answer

Assign a system-assigned managed identity to the Azure AI service.

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Deploy Azure Firewall to inspect outbound traffic.

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Enable public network access from selected IP addresses.

Question 15

A company uses Azure AI Document Intelligence to extract data from invoices. Recently, extraction accuracy dropped for new vendor formats. Which strategy should you implement to improve accuracy without retraining the entire model?

Accepted Answer

Train a custom extraction model using labeled examples from the new vendor formats.. Training a custom extraction model using labeled examples from the new vendor formats allows Azure AI Document Intelligence to learn the specific layout and field patterns of those invoices without affecting the prebuilt model's performance on other formats. This approach leverages the custom model training capability, which is designed to adapt to unique document structures while preserving the existing extraction logic for previously supported formats.

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Increase the confidence threshold for extraction results.

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Switch from Document Intelligence to Azure AI Language service.

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Increase the number of transactions per second (TPS) limit.