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Refer to the Exhibit Practice Questions

Practise Microsoft Azure AI Engineer Associate AI-102 practice questions — original exam-style scenarios covering every exam domain, with detailed explanations, wrong-answer analysis, and common exam traps.

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Scenario guide

How to approach refer to the exhibit practice questions

Practise exhibit-style questions that ask you to read a topology, table, command output or diagram before choosing the best answer.

Quick answer

Exhibit-style questions test whether you can read a topology, command output, diagram or table before choosing the best answer.

How to extract the relevant detail from an exhibit.

How topology, command output or routing information affects the answer.

How to avoid answering from memory before reading the evidence.

How to map the exhibit back to the exam objective.

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Practice set

Practice scenarios

Question 1mediummultiple choice
Full question →

Refer to the exhibit. You are configuring an agent in Azure AI Foundry. The agent fails to start because the specified model is not available in the current Azure OpenAI resource. What should you do to resolve the issue?

Exhibit

{
  "configurations": {
    "default": [
      {
        "model": {
          "provider": "AzureOpenAI",
          "name": "gpt-4",
          "version": "0613"
        },
        "connection_type": "Strong",
        "system_prompt": "You are an AI assistant..."
      }
    ]
  }
}
Question 2hardmultiple choice
Full question →

Refer to the exhibit. You receive this error when calling an Azure Cognitive Services API. What is the most likely cause?

Exhibit

{
  "error": {
    "code": "403",
    "message": "Access denied due to invalid subscription key. Make sure to provide a valid key for an active subscription.",
    "innererror": {
      "code": "InvalidSubscriptionKey",
      "message": "The provided subscription key is not valid for the Cognitive Services resource."
    }
  }
}
Question 3hardmultiple choice
Full question →

Refer to the exhibit. You are deploying an AI project in Microsoft Foundry using an ARM template. The deployment fails with an error indicating that the hub resource is not in the same region. What is the most likely cause?

Exhibit

{
  "name": "my-ai-project",
  "location": "eastus",
  "identity": {
    "type": "SystemAssigned"
  },
  "properties": {
    "aiResourceType": "Project",
    "hubResourceId": "/subscriptions/.../resourceGroups/.../providers/Microsoft.MachineLearningServices/workspaces/my-ai-hub"
  }
}
Question 4easymultiple choice
Full question →

You are testing an Azure OpenAI model with the parameters shown in the exhibit. The model generates very short responses. Which parameter should you modify to allow longer responses?

Exhibit

Refer to the exhibit.

temperature: 0.7
top_p: 0.9
max_tokens: 50
frequency_penalty: 0
presence_penalty: 0
Question 5hardmultiple choice
Full question →

Refer to the exhibit. You are troubleshooting an Azure OpenAI API call that is returning incomplete responses. The response stops mid-sentence. Which parameter should you adjust?

Exhibit

{
  "model": "gpt-4",
  "messages": [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "What is the capital of France?"}
  ],
  "max_tokens": 500,
  "temperature": 0.7,
  "top_p": 0.95,
  "frequency_penalty": 0,
  "presence_penalty": 0,
  "stop": null
}
Question 6mediummultiple choice
Full question →

Refer to the exhibit. An administrator runs this Azure CLI command to deploy a GPT-4 model in Azure AI Foundry. The command fails with an error that the deployment name already exists. What should the administrator do to resolve the issue?

Network Topology
name myFoundryresource-group rg-aideployment-name gpt-4model-name gpt-4model-version 0613sku-name Standardsku-capacity 10Refer to the exhibit.
Question 7mediummultiple choice
Full question →

Refer to the exhibit. You submit this request to Azure AI Language's conversational language understanding (CLU) for the 'FlightBooking' project. The model correctly identifies the intent as 'BookFlight' and extracts entities: 'Seattle' as FromCity, 'New York' as ToCity, and 'June 15th' as Date. What is the next step for the application?

Exhibit

Refer to the exhibit.
```json
{
  "kind": "Conversation",
  "analysisInput": {
    "conversationItem": {
      "id": "1",
      "participantId": "user",
      "text": "Book a flight from Seattle to New York on June 15th."
    }
  },
  "parameters": {
    "projectName": "FlightBooking",
    "deploymentName": "production",
    "stringIndexType": "TextElement_V8"
  }
}
```
Question 8hardmultiple choice
Full question →

Refer to the exhibit. You are configuring a system message for an Azure OpenAI deployment. The assistant is still generating harmful code despite the instruction. Which additional measure should you implement?

Exhibit

{
  "role": "system",
  "content": "You are an AI assistant that generates code. When asked to write code, always include comments explaining the code. If the user asks for something harmful, refuse and suggest an alternative."
}
Question 9easymultiple choice
Full question →

Refer to the exhibit. You are using Microsoft Graph to retrieve user information for use in a Microsoft 365 Copilot extension. The response shows that the mail and mobilePhone fields are null. What is the most likely reason?

Exhibit

{
  "@odata.context": "https://graph.microsoft.com/v1.0/$metadata#users/$entity",
  "id": "87d349ed-44d7-43e1-9a83-5f2406dee5bd",
  "displayName": "John Doe",
  "userPrincipalName": "john.doe@contoso.com",
  "businessPhones": [],
  "mobilePhone": null,
  "jobTitle": null,
  "mail": null
}
Question 10mediummultiple choice
Full question →

Refer to the exhibit. You are deploying an agent in Microsoft Foundry using the ARM template snippet above. The agent needs to call Microsoft Graph API to reset a user's password. However, the deployment fails with an authorization error. What is the most likely cause?

Exhibit

{
  "type": "Microsoft.Agents/agent",
  "apiVersion": "2025-01-01-preview",
  "properties": {
    "displayName": "SupportAgent",
    "description": "Agent for IT support",
    "actions": [
      {
        "type": "conversation",
        "id": "resetPassword",
        "authentication": {
          "type": "ManagedIdentity",
          "resourceId": "/subscriptions/.../userAssignedIdentities/support-identity"
        },
        "parameters": {
          "endpoint": "https://graph.microsoft.com/v1.0/users/{userId}/resetPassword",
          "method": "POST"
        }
      }
    ],
    "knowledgeStores": [
      {
        "type": "azureAISearch",
        "connectionReference": "search-connection"
      }
    ]
  }
}
Question 11hardmultiple choice
Full question →

Refer to the exhibit. You deployed a custom model for Language service. Which command should you run to check if the deployment is ready to accept inference requests?

Network Topology
resource-group myRGname myLangServicedeployment-name myDeploymentmodel-name myModelmodel-version 2023-04-15sku capacity 1"name": "myDeployment","model": {"name": "myModel","version": "2023-04-15"},"sku": {"name": "Standard","capacity": 1"status": "Succeeded""status": "Succeeded","properties": {"provisioningState": "Succeeded"
Question 12hardmultiple choice
Full question →

Refer to the exhibit. You are configuring an Azure OpenAI Service deployment for document summarization. The current parameters produce summaries that are often too verbose. You need to make the summaries more concise while maintaining factual accuracy. Which parameter change should you make?

Exhibit

{
  "completions": [
    {
      "prompt": "Generate a summary of the following text: ...",
      "parameters": {
        "temperature": 0.3,
        "max_tokens": 150,
        "top_p": 0.9,
        "frequency_penalty": 0.0,
        "presence_penalty": 0.0
      },
      "response": "..."
    }
  ]
}
Question 13hardmultiple choice
Full question →

Refer to the exhibit. A developer is configuring a QnA Maker skill for a bot. The skill fails to respond to queries. What is the most likely issue?

Exhibit

{
  "name": "QnA-Maker-Skill",
  "description": "QnA Maker skill for FAQ",
  "modelUrl": "https://westus.api.cognitive.microsoft.com/qnamaker/v4.0",
  "endpointKey": "abc123",
  "kbId": "def456"
}
Question 14mediummultiple choice
Full question →

Refer to the exhibit. You have trained an object detection model in Azure Custom Vision. The model is published as 'defect-model'. You need to deploy this model to a Docker container for on-premises inference using the Azure IoT Edge runtime. What should you do first?

Exhibit

{
  "customvision": {
    "project": {
      "name": "DefectDetection",
      "type": "ObjectDetection",
      "domain": "General",
      "exportable": true
    },
    "training": {
      "iteration": {
        "name": "Iteration 5",
        "publishName": "defect-model",
        "status": "Completed",
        "performance": {
          "precision": 0.85,
          "recall": 0.78,
          "mAP": 0.82
        }
      }
    }
  }
}
Question 15hardmultiple choice
Full question →

Refer to the exhibit. A developer tries to deploy a custom speech model but receives an error. What should the developer do to resolve the issue?

Network Topology
resource-group rgname mySpeechdeployment-name myModelmodel-format CustomSpeechmodel-name myCustomModelmodel-version latest"id": "/subscriptions/.../deployments/myModel","name": "myModel","properties": {"provisioningState": "Failed","error": {"code": "ModelUnsupported",

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