AI-103 Practice Test 30 — 15 Questions

Question 1

You are deploying an Azure OpenAI model in Azure AI Foundry and want to evaluate its performance and safety against a validation dataset before moving to production. Which tool should you use?

Accepted Answer

Model evaluation in Azure AI Foundry. Azure AI Foundry evaluation tools allow developers to run automated evaluations using metrics like groundedness, relevance, and coherence against test datasets.

Answer

Azure Monitor Log Analytics query packs

Answer

Azure Advisor cost recommendations

Answer

Azure API Management developer portal

Question 2

You are implementing indirect prompt injection protection for an agent that reads emails and summarizes them. An incoming email contains malicious instructions designed to trick the agent into exfiltrating user data. Which Azure AI feature should you configure to detect this threat?

Accepted Answer

Prompt Shields for indirect prompt injection in Azure AI Content Safety. Prompt Shields in Azure AI Content Safety include detection for indirect prompt injections, identifying when untrusted data sources attempt to hijack agent behavior.

Answer

Azure DDoS Protection standard tier

Answer

Azure Web Application Firewall (WAF) SQL injection rules

Answer

Microsoft Defender for Cloud threat detection

Question 3

Your organization operates in a highly regulated financial sector. You are required to ensure that all data stored by your Azure AI Custom Vision project is encrypted using a custom encryption key managed by your team in Azure Key Vault, rather than a Microsoft-managed key. Which feature must you configure during resource creation?

Accepted Answer

Customer-Managed Keys (CMK) with Azure Key Vault. Customer-managed keys (CMK) using Azure Key Vault allow organizations to control their encryption keys for Azure AI Services.

Answer

Storage Account Shared Access Signatures (SAS)

Answer

Microsoft Defender for Key Vault threat detection

Answer

Azure Information Protection sensitivity labels

Question 4

Your enterprise organization provisions multiple Azure AI Services accounts across different subscriptions. Security mandates that all API keys must be automatically rotated every 30 days without human intervention. Which Azure service configuration should you implement?

Accepted Answer

Azure Key Vault automated secret rotation using an Azure Function. Azure Key Vault integrates with managed identities and Event Grid or Azure Automation to automate secret and API key rotation schedules.

Answer

Microsoft Defender for Cloud JIT access policies

Answer

Azure AI Services built-in automatic key rotation policy

Answer

Azure Monitor alert rules tied to Microsoft Entra ID

Question 5

Your organization is running multiple Azure AI services. You need to configure alerts so that when the availability of any AI service drops below 99.% over a 15-minute window, an incident is created in ServiceNow. Which Azure Monitor feature should you use?

Accepted Answer

Azure Monitor metric alerts combined with Action Groups configured with a Webhook receiver. Azure Monitor metric alerts integrated with Action Groups allow sending notifications to webhooks (such as ServiceNow).

Answer

Azure Cost Management alerts

Answer

Azure Advisor performance recommendations

Answer

Microsoft Defender for Cloud threat detection

Question 6

You are provisioning an Azure AI services account and need to select the kind of resource. Which kind parameter value should you select for an Azure OpenAI deployment?

Accepted Answer

OpenAI. The 'OpenAI' kind is specified when creating Azure OpenAI resources.

Answer

CognitiveSearch

Answer

MachineLearning

Answer

BotService

Question 7

You are using Azure AI Document Intelligence to extract information from identity documents, such as passports and driver licenses. Which prebuilt model should you select?

Accepted Answer

prebuilt-idDocument. The prebuilt ID document model (prebuilt-idDocument) is designed to extract fields from passports and driver licenses.

Answer

prebuilt-tax.us.w2

Answer

prebuilt-W2

Answer

prebuilt-businessCard

Question 8

You are training a Custom Template model using Azure AI Document Intelligence. Your training dataset contains documents with multiple pages where the tables span across page breaks. How should you structure your training labels to handle multi-page tables correctly?

Accepted Answer

Label the table rows across pages using the same table index and consistent headers so the model recognizes the continuation.. When training a custom template model, tables that span multiple pages must be labeled continuously with consistent table IDs across page breaks so the model learns to associate them as a single logical table.

Answer

Create a separate table label for each page fragment and concatenate them via post-processing code.

Answer

Exclude multi-page tables from the training set and rely solely on the prebuilt layout model for tables.

Answer

Convert all multi-page documents into single extremely long virtual pages before labeling.

Question 9

You are troubleshooting an Azure AI Language resource deployment. Which THREE error codes or HTTP status codes might indicate an issue with your API request structure or payload? (Choose three.)

Accepted Answer

404 Not Found. HTTP 400 (Bad Request) indicates malformed JSON or invalid parameters, HTTP 404 indicates an incorrect endpoint URL, and HTTP 422 indicates unprocessable data. HTTP 200 is success.

Answer

100 Continue

Answer

200 OK

Question 10

You are implementing a text classification pipeline using Azure AI Language. You want to deploy your trained custom model to a production endpoint. What is required before you can assign traffic to the model deployment in Language Studio?

Accepted Answer

You must successfully complete model training and create a deployment in Language Studio.. Before a custom model can be deployed and used for inference, it must be successfully trained, and then assigned to a deployment name.

Answer

You must export the model container and deploy it to an Azure Kubernetes Service (AKS) cluster.

Answer

You must submit a support ticket to Microsoft to enable custom model endpoints.

Answer

You must convert the model files to ONNX format.

Question 11

When analyzing documents using Azure AI Document Intelligence, which THREE properties can be found within the returned JSON result object for an extracted table cell? (Choose THREE)

Accepted Answer

columnIndex. Table cell objects contain properties such as rowIndex, columnIndex, content, and boundingRegions.

Answer

audioTranscript

Answer

sentimentScore

Question 12

You are extracting data from tables. The layout model is missing specific column headers. How can you improve the results?

Accepted Answer

Use a Custom Neural model. Training a custom model allows you to define specific fields, including complex table structures.

Answer

Increase image resolution

Answer

Use the Read API

Answer

Enable 'document-classify' feature

Question 13

You are developing a solution that uses custom text classification in Azure AI Language. You choose the multi-label classification architecture. What is the key characteristic of multi-label text classification?

Accepted Answer

A single document can be assigned zero, one, or multiple categories simultaneously.. In multi-label classification, a single document can be assigned zero, one, or multiple distinct category labels simultaneously.

Answer

Each document must be assigned to exactly one mutually exclusive category.

Answer

The output is restricted to binary positive or negative values.

Answer

Categories are automatically generated by the service without user training data.

Question 14

You are configuring an Azure AI Document Intelligence custom extraction pipeline that processes thousands of diverse medical forms daily. You notice that extraction confidence scores for certain hand-written fields are low. What is the most effective remediation step within the Document Intelligence workflow?

Accepted Answer

Add additional labeled training documents that specifically feature diverse handwriting samples for those low-confidence fields.. Adding more high-quality, representative labeled training samples containing diverse handwriting styles directly improves custom model performance and confidence on ambiguous fields.

Answer

Disable the OCR engine parameter in the API call to bypass text recognition steps.

Answer

Decrease the model training iterations configuration setting to prevent overfitting on handwriting.

Answer

Switch from a Custom Neural model to a Custom Template model.

Question 15

You are integrating Document Intelligence with Azure Blob Storage. You need to provide the model with a set of documents for training. How should you prepare the data?

Accepted Answer

Upload files and corresponding .labels.json and .ocr.json files. Training requires documents to be stored in an Azure Blob Storage container with associated .labels.json files generated by the labeling tool.

Answer

Convert all files to CSV

Answer

Store files in an Azure SQL database

Answer

Upload raw files only