AI-102 Plan and manage an Azure AI solution Practice Test 3 — 15 Questions

Question 1

You are deploying an Azure AI Search solution that indexes customer support tickets. The solution must support fuzzy search for misspelled keywords and boost results from premium customers. Which two features should you configure?

Accepted Answer

Scoring profiles. Scoring profiles allow you to boost search results based on specific criteria, such as customer tier, by assigning higher weights to certain fields or adding functions that increase scores for premium customers. This directly supports the requirement to prioritize results from premium customers.

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Synonym maps

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Suggesters

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Custom analyzers

Question 2

Your company uses Azure OpenAI Service to generate product descriptions. You need to ensure that the generated content does not include offensive language and adheres to responsible AI principles. What should you implement?

Accepted Answer

Configure content filters in Azure OpenAI. Content filters in Azure OpenAI allow you to define categories (e.g., hate, violence, self-harm) and severity levels (low, medium, high) to automatically block or flag offensive language in generated outputs. This directly enforces responsible AI principles by preventing harmful content from being surfaced to users, without requiring model retraining or encryption changes.

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Enable customer-managed key encryption

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Fine-tune the model with a curated dataset

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Set usage limits and throttling

Question 3

A team is building a chatbot using Azure Bot Service and Language Understanding (LUIS). The chatbot must handle multiple languages. What should you configure?

Accepted Answer

Create separate LUIS applications for each language. Option D is correct because LUIS does not natively support multilingual models within a single app. Each LUIS application is designed for a single language, so to handle multiple languages, you must create separate LUIS apps—one per language—and route user utterances to the appropriate app based on the detected language. This ensures accurate intent and entity recognition tailored to each language's linguistic patterns.

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Configure a single LUIS app with multilingual utterances

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Use Azure AI Search to index translated content

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Use Azure Translator to translate utterances before calling LUIS

Question 4

Refer to the exhibit. You are configuring an Azure AI Foundry agent for customer support. The agent uses Azure AI Search for retrieval and Azure OpenAI for generation. Users report that the agent provides correct answers but sometimes includes inappropriate language. What is the most likely cause?

Accepted Answer

The content safety blocklist is not applied to the chat output. The content safety threshold is set to 'high', which is the most restrictive level. Option B is correct because 'high' threshold blocks more content, but the issue is inappropriate language, so the threshold might be too low if it allows offensive content; actually, 'high' is strict, so the issue is that the content safety is not applied to the generation output. Option A is wrong because semantic search is for relevance, not safety. Option C is wrong because the deployment name is irrelevant. Option D is wrong because the system message does not guarantee safety filtering.

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The OpenAI deployment 'gpt-4o' does not support content filtering

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The content safety threshold should be set to 'low' to block more content

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The semantic configuration is not optimized for safety

Question 5

You are responsible for an Azure AI solution that uses Custom Vision to classify manufacturing defects. The model must achieve high recall to avoid missing defects. The current model has high precision but low recall. Which action should you take?

Accepted Answer

Lower the probability threshold for the defect class. Lowering the probability threshold for the defect class means the model will classify an image as defective even when its confidence score is lower. This increases the number of true positives (defects caught), directly improving recall at the cost of potentially more false positives. In Custom Vision, the default probability threshold is 50%, and adjusting it downward is the standard technique to prioritize recall over precision.

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Add more images of non-defective items to the training set

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Increase the number of training iterations

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Increase the probability threshold for the defect class

Question 6

Your organization wants to implement a document processing pipeline that extracts text from scanned PDFs and identifies named entities. Which two Azure AI services should you use?

Accepted Answer

Azure AI Language. Azure AI Document Intelligence (formerly Form Recognizer) is used to extract text from scanned PDFs via OCR, while Azure AI Language provides pre-built named entity recognition (NER) to identify entities like people, organizations, and locations. Together, they form a complete pipeline: Document Intelligence handles the image-to-text conversion, and Language processes the extracted text for entity extraction.

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Azure AI Custom Vision

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Azure AI Translator

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Azure AI Speech

Question 7

A company uses Azure AI Search to index product catalogs. The search must support multilingual queries and return results in the user's language. What should you configure?

Accepted Answer

Assign appropriate language analyzers to fields. Azure AI Search allows you to assign language-specific analyzers (e.g., Microsoft English, French, Arabic) to individual fields in the index. When a query is submitted, the search engine uses the analyzer associated with the field to tokenize and normalize the text according to the linguistic rules of that language, enabling accurate multilingual search and returning results in the user's language.

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Create synonym maps for each language

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Configure scoring profiles based on language

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Enable semantic search

Question 8

You deploy a Custom Vision object detection model to classify vehicles. The model works well in good lighting but fails in low-light conditions. What is the most appropriate action?

Accepted Answer

Add images with different lighting conditions to the training set. Option A is correct because the core issue is a data distribution mismatch: the model was trained primarily on well-lit images and lacks exposure to low-light examples. Adding images with diverse lighting conditions directly addresses this by enriching the training dataset, enabling the model to learn robust features for low-light scenarios. This aligns with the fundamental principle that Custom Vision models are only as good as the training data they receive.

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Increase the probability threshold

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Increase the number of training iterations

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Use a domain-specific model for vehicles

Question 9

Your chatbot uses Azure Bot Service and QnA Maker. Users can ask questions in natural language, and the bot returns answers from a knowledge base. Users report that the bot sometimes returns irrelevant answers. What should you do first?

Accepted Answer

Review and edit the QnA pairs to add alternative phrasings. The core issue is that the bot returns irrelevant answers because the QnA Maker knowledge base lacks sufficient alternative phrasings to match the variety of user questions. By reviewing and editing QnA pairs to add alternative phrasings, you directly improve the synonym and paraphrase coverage, which increases the confidence score for correct matches and reduces irrelevant responses. This is the first and most fundamental troubleshooting step before considering more complex integrations.

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Create multiple QnA Maker knowledge bases for different topics

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Integrate LUIS to detect user intent

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Use Azure AI Search to index the knowledge base

Question 10

Refer to the exhibit. You are using Azure OpenAI to build a trivia bot. The bot responds correctly to simple questions but sometimes gives overly verbose or off-topic answers. Which parameter should you adjust to make responses more focused?

Accepted Answer

Decrease temperature. Decreasing the temperature parameter reduces the randomness of the model's output, making it more deterministic and focused. For a trivia bot that gives overly verbose or off-topic answers, lowering temperature (e.g., from 0.7 to 0.3) forces the model to choose higher-probability tokens, which typically correspond to more concise and relevant responses.

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Increase temperature

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Decrease top_p

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Increase max_tokens

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Decrease max_tokens

Question 11

You manage an Azure AI Search service that indexes legal documents. The search latency is high, and you need to improve query performance without reducing index size. Which action should you take?

Accepted Answer

Increase the number of replicas. Increasing the number of replicas distributes query load across multiple copies of the index, which directly improves query throughput and reduces latency. Replicas are designed for scaling query operations without changing the index size or storage capacity.

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Upgrade to a higher pricing tier

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Increase the number of partitions

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Reduce the number of searchable fields

Question 12

A healthcare organization uses Azure AI Language to extract medical entities from clinical notes. The solution must comply with HIPAA. What should you configure?

Accepted Answer

Use Azure AI Language with HIPAA-enabled service and enable encryption. Option A is correct because Azure AI Language can be configured with a HIPAA-eligible service tier, and enabling encryption at rest and in transit ensures compliance with HIPAA's security and privacy rules. This configuration meets the healthcare organization's requirement to protect protected health information (PHI) when extracting medical entities from clinical notes.

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Configure data residency to a specific region

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Enable content filtering

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Isolate the service in a virtual network

Question 13

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.

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The location is not specified correctly

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The pricing tier S0 does not support network restrictions

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The custom subdomain name is not globally unique

Question 14

Your company uses Azure OpenAI to generate code snippets. Developers need to ensure that the generated code does not contain security vulnerabilities. What should you implement?

Accepted Answer

Integrate a static code analysis tool into the CI/CD pipeline to scan generated code. Option D is correct because integrating a static code analysis tool (e.g., Microsoft Defender for DevOps, SonarQube, or Checkmarx) into the CI/CD pipeline allows automated scanning of generated code for security vulnerabilities before deployment. This approach directly addresses the requirement to ensure generated code is free of vulnerabilities, as Azure OpenAI content filters are not designed to detect code-level security flaws like SQL injection or buffer overflows.

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Set usage quotas to limit the number of code generation requests

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Fine-tune the model on a dataset of secure code examples

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Configure Azure OpenAI content filters to block vulnerable code

Question 15

Your team develops a document translation solution using Azure AI Translator. The solution must translate documents while preserving formatting and layout. Which feature should you use?

Accepted Answer

Azure AI Translator Document Translation. Azure AI Translator Document Translation is specifically designed to translate entire documents while preserving the original formatting, structure, and layout. Unlike Text Translation, which handles only plain text strings, Document Translation processes files (e.g., PDF, Word, Excel) and returns a translated version with the same formatting, making it the correct choice for this requirement.

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Azure AI Translator Custom Translator

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Azure AI Document Intelligence

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Azure AI Translator Text Translation