AI-102 Practice Test 11 — 15 Questions

Question 1

Refer to the exhibit. You deploy an Azure AI Services multi-service account using this ARM template. After deployment, developers cannot access the service from their local machines. What is the most likely reason?

Accepted Answer

The network ACLs block all traffic by default. The ARM template for an Azure AI Services multi-service account includes a `networkAcls` property with `defaultAction` set to `Deny`. This configuration blocks all traffic by default, including requests from developers' local machines, unless an explicit IP rule or virtual network rule is added to allow access. Since no such rules are shown in the exhibit, the network ACLs are the most likely cause of the connectivity failure.

Answer

The location is not specified correctly

Answer

The pricing tier S0 does not support network restrictions

Answer

The custom subdomain name is not globally unique

Question 2

Your company uses Azure OpenAI Service to generate marketing content. You need to ensure that the generated content does not contain offensive language. Which feature should you enable?

Accepted Answer

Azure AI Content Safety filters.. Azure AI Content Safety filters are specifically designed to detect and block offensive, inappropriate, or harmful language in text and images. By enabling these filters on your Azure OpenAI Service deployment, you can configure severity thresholds for categories like hate, self-harm, sexual, and violence content, ensuring generated marketing content meets safety policies.

Answer

Audit logging for all API calls.

Answer

Data encryption at rest.

Answer

Rate limiting on the endpoint.

Question 3

Which TWO monitoring metrics should you track to ensure the health and performance of an Azure AI Search service used for a customer-facing product catalog?

Accepted Answer

Throttled search queries count.. Throttled search queries count (Option A) is a critical health metric because it directly indicates when the search service is under excessive load, causing requests to be rate-limited. For a customer-facing product catalog, throttling degrades user experience and can lead to failed searches. Tracking this metric helps you decide when to scale up replicas or partitions to maintain service level agreements.

Answer

Indexer execution history and duration.

Answer

Storage used in GB.

Answer

Number of successful search requests.

Question 4

Which TWO actions are required to enable private endpoint connectivity for an Azure AI Language resource?

Accepted Answer

Disable public network access on the AI resource. Private endpoint requires a subnet in a VNet and disabling public network access. Option A is wrong because private DNS zone is optional but recommended. Option D is wrong because service tags are not required. Option E is wrong because firewall rules are not needed.

Answer

Configure an Azure Firewall rule to allow the private endpoint

Answer

Create a private DNS zone for the resource

Answer

Add a service tag to the network security group

Question 5

Which TWO actions are recommended to secure an Azure AI Language resource?

Accepted Answer

Use managed identities for authentication from Azure services. Managed identities allow Azure AI Language resources to authenticate to other Azure services (like Azure Storage or Azure Key Vault) without storing credentials in code or configuration. This eliminates the risk of access key leakage and aligns with the principle of least privilege, as the identity is tied to the resource lifecycle and can be granted granular RBAC permissions.

Answer

Enable local authentication with access keys

Answer

Allow all Azure services through the firewall

Answer

Enable anonymous access for public APIs

Question 6

Which TWO Azure services can be used to monitor and analyze the usage costs of an Azure AI solution that includes multiple Cognitive Services accounts?

Accepted Answer

Azure Cost Management + Billing. Azure Cost Management + Billing (C) provides native tools to track, analyze, and optimize cloud spending across all Azure services, including multiple Cognitive Services accounts. It allows you to break down costs by resource, resource group, or tag, and set budgets with alerts. Azure Monitor metrics and logs (E) can capture custom metrics and diagnostic logs from Cognitive Services, enabling you to correlate usage patterns with cost data for deeper analysis.

Answer

Azure Service Health

Answer

Azure Policy

Answer

Azure Advisor

Question 7

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?

Accepted Answer

Deploy the gpt-4-0613 model in the Azure OpenAI resource. The agent fails to start because the specified model (likely gpt-4-0613) is not deployed in the Azure OpenAI resource. In Azure AI Foundry, agents require an existing model deployment to invoke; you cannot use a model that hasn't been deployed. Option B correctly resolves this by deploying the required model in the Azure OpenAI resource.

Answer

Modify the system_prompt to include the model version

Answer

Change the connection_type to 'Weak'

Answer

Change the provider to 'AzureAI'

Question 8

You are responsible for managing costs for Azure AI services used by multiple teams. You notice that costs are higher than expected. Which two actions should you take to reduce costs without impacting performance?

Accepted Answer

Set up budgets and alerts in Cost Management.. Option A is correct because setting up a budget alert helps monitor spending. Option C is correct because choosing a tier that matches actual usage avoids overpaying. Option B is wrong because it does not reduce costs. Option D is wrong because deactivating resources would impact performance.

Answer

Migrate all services to a higher tier for better performance.

Answer

Deactivate unused resources to save costs.

Question 9

Refer to the exhibit. You deployed a Conversational Language Understanding (CLU) project. A user says 'hi, where is my order?' The model returns a single intent 'Greeting' with confidence 0.85. You need the model to detect both intents. What should you change?

Accepted Answer

Set 'multipleIntents' to true.. Option C is correct because the Conversational Language Understanding (CLU) service supports multi-intent detection only when the 'multipleIntents' flag is explicitly set to true in the project settings. By default, CLU returns only the highest-confidence intent; enabling this flag allows the model to return all intents whose confidence exceeds the threshold, enabling detection of both 'Greeting' and 'OrderStatus' from a single utterance.

Answer

Lower the confidenceThreshold to 0.5.

Answer

Add more utterances to the 'OrderStatus' intent.

Answer

Change the project kind to 'Orchestration'.

Question 10

You need to implement content moderation for a social media platform using Azure AI Content Safety. The solution must block hate speech and self-harm content while allowing mild profanity. Which configuration should you use?

Accepted Answer

Enable hate speech and self-harm with severity threshold 4; enable profanity with severity threshold 6. Option D is correct because Azure AI Content Safety allows you to set severity thresholds per category (0-6). By enabling hate speech and self-harm with a threshold of 4, you block content at severity level 4 or higher (e.g., severe hate speech and self-harm), while enabling profanity with a threshold of 6 means only the most extreme profanity (level 6) is blocked, allowing mild profanity through. This matches the requirement to block hate speech and self-harm but allow mild profanity.

Answer

Enable all categories with severity threshold 0 (block all)

Answer

Enable all categories with severity threshold 2

Answer

Enable hate speech and self-harm categories; disable profanity

Question 11

You are configuring semantic search in Azure AI Search. Based on the exhibit, which field is used as the title field for semantic ranking?

Accepted Answer

title. Option C is correct because in Azure AI Search semantic ranking, the 'title' field is designated as the primary field for semantic ranking. This field provides a concise, high-level summary of the document content, which the semantic ranker uses to understand the document's main topic and improve relevance scoring. The semantic configuration references this field via the 'titleField' parameter in the semantic configuration object.

Answer

my-semantic-config

Answer

description

Answer

prioritizedKeywordsFields

Question 12

You are designing a chatbot using Azure AI Language. The chatbot must understand user intents and also extract entities like dates and locations. Which feature combination should you use?

Accepted Answer

Conversational Language Understanding (CLU) with entities. Conversational Language Understanding (CLU) is the correct Azure AI Language feature for building a chatbot that understands user intents and extracts entities like dates and locations. CLU is specifically designed for natural language understanding (NLU) tasks, providing prebuilt and custom entity extraction alongside intent recognition, which directly matches the requirement.

Answer

Sentiment analysis and entity linking

Answer

Custom text classification and key phrase extraction

Answer

Orchestration Workflow and custom text classification

Question 13

You are developing a chatbot that uses Azure AI Language to understand user intents. The chatbot must handle multiple languages and direct users to the appropriate support team based on the detected intent. Which Azure AI Language feature should you use?

Accepted Answer

Conversational language understanding (CLU). Conversational language understanding (CLU) is the correct feature because it is specifically designed to extract intents and entities from user utterances in a multi-language conversational context. CLU enables the chatbot to detect the user's intent (e.g., 'billing', 'technical support') and route them to the appropriate support team, while also supporting multiple languages through its language-agnostic model training and per-language project configurations.

Answer

Text Analytics

Answer

QnA Maker

Answer

Translator

Question 14

You are deploying an Azure AI Speech custom voice model. After training, the voice sounds unnatural. Which parameter should you adjust to improve naturalness?

Accepted Answer

Increase the training duration. Increasing the training duration (Option C) allows the custom voice model to learn more nuanced prosody, intonation, and phonetic patterns from the training data, directly improving naturalness. Azure AI Speech's custom neural voice (CNV) training uses deep neural networks that benefit from extended epochs to reduce overfitting and enhance voice quality.

Answer

Change the audio output format to 48 kHz

Answer

Increase the speaking rate

Answer

Use a different language for the training data

Question 15

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

Answer

Azure AI Translator

Answer

Azure AI Search

AI-102 Practice Test 11 — 15 Questions

Exhibit

AI-102 Practice Test 11 — 15 Questions

Exhibit