AI-102 Plan and manage an Azure AI solution Practice Test 10 — 15 Questions

Question 1

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?

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

Accepted Answer

Enable hate speech and self-harm with severity threshold 4; enable profanity with severity threshold 6. 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)

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Enable all categories with severity threshold 2

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Enable hate speech and self-harm categories; disable profanity

Question 2

Your Azure AI Search index stores customer support tickets. You need to implement a search feature that returns semantically similar results even if the query uses different wording. Which configuration should you enable?

Accepted Answer

Enable semantic search and configure a semantic configuration. Semantic search in Azure AI Search uses deep neural networks to understand the intent and context of a query, returning results that are semantically similar even when the wording differs. By enabling semantic search and configuring a semantic configuration, you define which fields are used for summarization and ranking, which directly addresses the requirement for meaning-based matching rather than keyword matching.

Answer

Use simple query parsing with searchMode=any

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Add a synonym map with custom entries

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Enable fuzzy search on the index

Question 3

You are building a chatbot using Azure AI Bot Service and Language Service. The bot must recognize user intent for 'check order status'. How should you configure the Language Service?

Accepted Answer

Create a custom intent classification project. To recognize user intent for 'check order status', you need a custom intent classification project in Azure Language Service. This project type uses a trained model to map utterances to specific intents, such as 'CheckOrderStatus', which is exactly what the chatbot requires. Prebuilt models or QnA Maker do not provide custom intent recognition.

Answer

Deploy a QnA Maker knowledge base

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Configure a sentiment analysis endpoint

Answer

Use the prebuilt entity extraction model

Question 4

You need to analyze images to detect objects and read text from documents using a single Azure AI service. Which service should you use?

Accepted Answer

Azure AI Vision. Azure AI Vision is the correct choice because it provides both image analysis (object detection) and optical character recognition (OCR) for reading text from documents within a single service. Its Read API and Analyze Image API cover both requirements without needing separate services.

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Azure AI Document Intelligence (Form Recognizer)

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Azure AI Custom Vision

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Azure AI Language Service

Question 5

Your Azure AI Language custom entity recognition model incorrectly extracts 'Microsoft' as an organization when it refers to the company, but fails to extract 'Microsoft' as a product when it refers to the software. How should you improve the model?

Accepted Answer

Label 'Microsoft' as both 'Organization' and 'Product' in different training sentences with appropriate context. Custom entity recognition models in Azure AI Language learn to distinguish entity types based on context. By labeling 'Microsoft' as 'Organization' in sentences where it refers to the company and as 'Product' in sentences where it refers to the software, you provide the model with the contextual clues needed to disambiguate the same token across different uses. This supervised learning approach directly addresses the model's failure to recognize the product entity.

Answer

Reduce the amount of training data to avoid confusion

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Remove the 'Organization' entity type from the model

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Add more training sentences without labeling the entity type

Question 6

You need to create a solution that extracts key-value pairs from scanned invoices using Azure AI Document Intelligence. The invoices have varying layouts. Which model should you use?

Accepted Answer

Prebuilt invoice model. The Prebuilt invoice model (Option D) is specifically designed to extract key-value pairs, line items, and other structured fields from invoices, even when layouts vary. It is trained on thousands of invoice samples and uses deep learning to handle diverse formats without requiring custom training, making it the correct choice for this scenario.

Answer

Layout model

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Custom extraction model

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Read model

Question 7

Your Azure AI Search index contains millions of documents. Users report that search results are slow for complex queries. You need to improve query performance without reducing result quality. Which action should you take?

Accepted Answer

Increase the number of replicas. Increasing the number of replicas in Azure AI Search distributes query load across multiple copies of the index, enabling parallel processing of complex queries. This directly improves query throughput and latency without altering the index schema or reducing result quality, as replicas provide dedicated resources for query execution.

Answer

Reduce the maximum number of results returned per query

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Remove all facet fields from the index

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Disable complex query types such as fuzzy and regex

Question 8

Which THREE of the following are capabilities of Azure AI Content Safety?

Accepted Answer

Sexual content detection. Azure AI Content Safety is specifically designed to detect harmful content across four categories: sexual content, hate speech, self-harm, and violence. Option A is correct because sexual content detection is one of the four core content categories that the service is trained to identify, using multi-class classification models to flag explicit or suggestive material.

Answer

Sentiment analysis

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Personally identifiable information (PII) detection

Question 9

Which TWO of the following are best practices for managing Azure AI services costs?

Accepted Answer

Use the S0 pricing tier for production workloads. The S0 pricing tier is the standard paid tier for Azure AI services, such as Cognitive Services, and is designed for production workloads. It provides higher throughput, reliability, and support compared to lower tiers, making it a cost-effective choice for production scenarios where performance and availability are critical.

Answer

Always use the Free tier to avoid charges

Answer

Scale up partitions to improve performance

Answer

Increase batch size to reduce number of API calls

Question 10

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. 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

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description

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prioritizedKeywordsFields

Question 11

You are using Azure AI Language's conversational language understanding (CLU). The above JSON is a request to a CLU endpoint. What is the purpose of this request?

Accepted Answer

To predict the intent and entities from the user utterance. The JSON request is sent to the Azure AI Language CLU endpoint with a 'query' field containing the user utterance. The 'kind' field is set to 'Conversation', which triggers the CLU runtime to analyze the utterance against the deployed model. The purpose is to return a prediction of the top intent and any extracted entities, which is the core function of a conversational language understanding endpoint.

Answer

To query a knowledge base for answers

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To deploy the CLU model to production

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To train a new CLU model

Question 12

You run the above Azure CLI command. What is the expected output?

Accepted Answer

The primary and secondary keys. The Azure CLI command `az cognitiveservices account keys list` retrieves only the primary and secondary API keys for the Cognitive Services account. The endpoint is not included in the output; it must be obtained separately using `az cognitiveservices account show`. Therefore, the expected output contains the primary key and secondary key only.

Answer

The primary and secondary keys along with the endpoint

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A list of endpoints for the service

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An error because the command is incorrect

Question 13

You are designing an AI solution that uses Azure OpenAI Service to answer customer queries. The solution must ensure that the model does not generate harmful or inappropriate content. Which Azure AI service should you configure to enforce content safety policies?

Accepted Answer

Azure AI Content Safety. Azure AI Content Safety is the dedicated service for detecting and filtering harmful content such as hate speech, violence, self-harm, and sexual content. It provides configurable severity thresholds and can be integrated with Azure OpenAI Service to enforce content safety policies on model inputs and outputs. This ensures the AI solution meets responsible AI requirements without modifying the underlying model.

Answer

Azure AI Speech

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Azure OpenAI Service

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Azure AI Search

Question 14

Your company is deploying an Azure AI solution that uses multiple AI services. You need to ensure that all API calls are authenticated securely using managed identities. Which of the following steps is required to enable managed identity authentication for an Azure AI service?

Accepted Answer

Assign a managed identity to the Azure AI service and grant it the required RBAC role. Managed identity authentication for Azure AI services requires assigning either a system-assigned or user-assigned managed identity to the resource, and then granting that identity the appropriate RBAC role (e.g., Cognitive Services User) on the target AI service. This eliminates the need for keys or secrets in the code and leverages Azure AD tokens for secure, passwordless authentication.

Answer

Enable system-assigned managed identity at the subscription level

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Store the authentication key in Azure Key Vault and reference it in the application

Answer

Configure a shared access key in the Azure AI service

Question 15

You are planning an Azure AI solution that uses Azure AI Document Intelligence to extract data from invoices. The solution must handle large volumes of documents with varying layouts. Which pricing tier should you choose to ensure scalability and high throughput?

Accepted Answer

Standard (S0). The Standard (S0) tier is correct because Azure AI Document Intelligence requires the S0 tier for production workloads that demand high throughput and scalability across varying document layouts. The S0 tier supports unlimited transactions per second (TPS) with auto-scaling, whereas lower tiers impose strict rate limits or lack the capacity to handle large volumes of invoices with diverse formats.

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Premium (P0)

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Free (F0)

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Basic (B0)