AI-102 Plan and manage an Azure AI solution Practice Test 11 — 15 Questions

Question 1

You are reviewing the ARM template snippet for an Azure AI Foundry hub. After deployment, you notice that the hub cannot connect to the storage account. What is the most likely cause?

Accepted Answer

The hub uses a managed network that blocks outbound traffic to the storage account. The most likely cause is that the hub uses a managed network which, by default, blocks outbound traffic to the storage account unless explicitly allowed via outbound rules or private endpoints. Azure AI Foundry hubs enforce network isolation for security, and if the storage account is not configured as an approved destination, the hub cannot establish the required connections for data access.

Answer

The location 'eastus' does not support AI Foundry hubs

Answer

The storage account name contains invalid characters

Answer

The key vault is not configured with a firewall rule

Question 2

Your team is developing a chatbot using Azure AI Bot Service. You need to ensure that the bot can handle multiple languages and respond appropriately. Which Azure AI service should you integrate to perform language detection?

Accepted Answer

Azure AI Language. Azure AI Language provides pre-built language detection capabilities as part of its natural language processing (NLP) features. By integrating this service, the bot can analyze incoming text and identify the language, enabling it to route responses appropriately or trigger language-specific logic.

Answer

Azure AI Speech

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Azure AI Content Safety

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Azure AI Translator

Question 3

You are testing an Azure OpenAI Service chat completion with function calling. The assistant returned null content and a tool call. What does this indicate?

Accepted Answer

The model is using a tool to answer the question, so content is null. In Azure OpenAI Service function calling, when the model determines that it needs to invoke a tool (e.g., an external API or database query) to fulfill the user's request, it returns a `tool_calls` object with `content` set to `null`. This is the expected behavior—the model is signaling that it is delegating the response to the tool, not that it has failed or is blocked.

Answer

The model is unable to answer the question and returned an error

Answer

The system message is preventing the model from responding

Answer

The function call syntax is invalid and the model skipped it

Question 4

You are deploying a custom text classification model using Azure AI Language. The model must be retrained monthly with new labeled data. You need to automate the retraining process with minimal manual intervention. Which approach should you use?

Accepted Answer

Use the Azure AI Language REST API to trigger training and deployment on a schedule using Azure Logic Apps. Azure Logic Apps can schedule HTTP requests to the Azure AI Language REST API to trigger training and deployment of a custom text classification model. This approach automates the monthly retraining process without manual intervention, using the API's capabilities for model creation, training, and deployment.

Answer

Create an Azure DevOps pipeline that manually retrains the model every month

Answer

Retrain the model manually using Language Studio each month

Answer

Use Azure Machine Learning to host the custom model and automate retraining

Question 5

Your organization uses Microsoft Entra ID for identity management. You are building an AI solution that uses Azure AI Vision to analyze images. The solution must use managed identities to authenticate to the Vision resource. Which RBAC role should you assign to the managed identity?

Accepted Answer

Cognitive Services User. The Cognitive Services User role (B) is the correct RBAC role because it grants the minimum required permissions for a managed identity to call Azure AI Vision APIs (e.g., analyze image, OCR) without allowing any write or management operations. This role is specifically designed for accessing Azure Cognitive Services endpoints, and it aligns with the principle of least privilege for authentication via managed identities.

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Owner

Answer

Reader

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Contributor

Question 6

You are planning to use Azure AI Content Safety to moderate user-generated content in a social media application. The solution must detect hate speech and self-harm content. Which Content Safety features should you enable?

Accepted Answer

Hate and self-harm content filters. Azure AI Content Safety provides pre-built filters for specific harm categories, including hate speech and self-harm. Enabling the 'Hate and self-harm content filters' directly activates the detection models for these categories, meeting the requirement without needing custom categories or additional features.

Answer

Severity levels for all categories

Answer

Custom categories for hate speech and self-harm

Answer

Image moderation

Question 7

Which TWO actions should you take to ensure compliance with data residency requirements when using Azure AI services across multiple regions?

Accepted Answer

Configure the AI service's data residency settings to restrict data to the region. Azure AI services provide data residency settings that allow you to restrict data processing to a specific region, ensuring compliance with data residency requirements. Option E is correct because deploying separate instances of the AI service in each required region gives you full control over where data is stored and processed, which is a common pattern for meeting strict data residency mandates.

Answer

Use a global Azure AI service resource and configure geo-replication

Answer

Enable Azure Front Door to route traffic to the nearest region

Answer

Disable data replication for the AI service

Question 8

Which THREE factors should you consider when selecting the pricing tier for an Azure AI Language resource to handle a high-volume production workload?

Accepted Answer

Transactions per second (TPS) limits. The pricing tier for Azure AI Language directly determines the Transactions Per Second (TPS) limit, which is critical for high-volume production workloads. For example, the Free tier (F0) allows only 20 TPS, while Standard (S) tiers can scale to thousands of TPS depending on the selected SKU. Exceeding the TPS limit results in throttling (HTTP 429 errors), so selecting a tier with sufficient TPS capacity is essential to maintain throughput under load.

Answer

Language support

Answer

SLA percentage

Question 9

Which TWO Azure AI services can you use to implement a custom question-answering system?

Accepted Answer

Azure OpenAI Service. Azure OpenAI Service is correct because it provides access to GPT models that can be fine-tuned or used with custom prompts to build a question-answering system. By leveraging the 'chat completions' API with a system message and context documents, you can implement a custom Q&A system that generates answers based on your proprietary data.

Answer

Azure AI Bot Service

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Azure AI Translator

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Azure AI Search

Question 10

You executed the Azure CLI command to list Azure OpenAI resources. You need to programmatically access the endpoint of the resource named 'gpt4' in a script. What is the most reliable way to extract the endpoint?

Accepted Answer

Use az cognitiveservices account show with --query to filter by name. `az cognitiveservices account show` with the `--query` parameter allows you to retrieve the specific endpoint property for a named resource using JMESPath filtering. This approach is reliable, scriptable, and avoids parsing unstructured output, which is error-prone. The Azure CLI returns structured JSON, and `--query` extracts the exact value without manual string manipulation.

Answer

Use Azure PowerShell Get-AzCognitiveServicesAccount cmdlet

Answer

Parse the table output using string manipulation

Answer

Deploy a new Azure OpenAI resource with a known endpoint

Question 11

You are reviewing the response from an Azure OpenAI Service chat completion API call. The finish_reason is 'stop'. What does this indicate?

Accepted Answer

The model completed the response naturally. The `finish_reason` field in the Azure OpenAI chat completion API response indicates why the model stopped generating tokens. A value of `'stop'` means the model encountered a natural stopping point, such as the end of a sentence or a logical conclusion, and completed the response without hitting any limits or filters.

Answer

The response was truncated because the token limit was reached

Answer

The response was blocked by the content filter

Answer

The model is still generating the response

Question 12

You need to monitor the costs of your Azure AI services across multiple subscriptions. Which Azure tool should you use to track spending and set budgets?

Accepted Answer

Azure Cost Management. Azure Cost Management is the dedicated tool for monitoring, analyzing, and controlling cloud spending across multiple subscriptions. It provides cost analysis, budget creation, and alerting capabilities specifically designed for tracking Azure AI services costs at scale.

Answer

Azure Portal

Answer

Azure Monitor

Answer

Azure Advisor

Question 13

You are deploying an Azure AI Language service custom text classification model. You need to ensure that the training data is balanced and representative. What should you do?

Accepted Answer

Split the labeled data into training and test sets, ensuring each class has similar proportions.. Splitting labeled data into training and test sets while ensuring each class has similar proportions (stratified split) is a standard practice for balanced and representative training data. This approach prevents class imbalance from skewing model evaluation metrics and ensures the model generalizes well to unseen data. In Azure AI Language custom text classification, this is critical for achieving reliable performance across all classes.

Answer

Use only the most frequent labels to train the model.

Answer

Oversample the minority classes to match the majority class size.

Answer

Use all labeled data for training and rely on cross-validation.

Question 14

Your company uses Azure OpenAI Service to generate product descriptions. You need to reduce costs while maintaining response quality for common requests. What should you implement?

Accepted Answer

Enable semantic caching to reuse responses for similar prompts.. Semantic caching stores responses for semantically similar prompts, allowing Azure OpenAI Service to return cached results for common requests without incurring per-token inference costs. This directly reduces costs while preserving response quality, as the cached responses are identical to what the model would generate. Unlike other options, it avoids degrading output quality or requiring architectural changes.

Answer

Use a smaller model variant (e.g., GPT-3.5 instead of GPT-4).

Answer

Batch multiple requests into a single API call.

Answer

Reduce the max_tokens parameter for all requests.

Question 15

You need to provide a business analyst with access to create and manage Azure AI Language projects without granting them full subscription-level permissions. What role should you assign?

Accepted Answer

Cognitive Services Language Owner at the resource level. The Cognitive Services Language Owner role at the resource level grants full permissions to create, read, update, and delete Azure AI Language projects and resources, including managing custom models and deployments, without granting any permissions outside that specific resource. This is the least-privilege role that satisfies the business analyst's need to manage Language projects while avoiding subscription-level access.

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Reader at the resource group level

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Contributor at the subscription level

Answer

Cognitive Services User at the resource level