AI-102 Practice Test 24 — 15 Questions

Question 1

You are using Azure OpenAI Service to generate marketing copy. You notice that the output sometimes contains factual inaccuracies about your company's products. Which action can you take to improve factual accuracy?

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

Accepted Answer

Include relevant product information in the system message.. Including relevant product information in the system message provides the model with authoritative context that grounds its responses in factual data. The system message acts as a persistent instruction set that the model uses to shape its outputs, reducing reliance on its internal training data which may be outdated or incomplete. This technique, known as 'grounding,' directly improves factual accuracy by supplying the model with the specific facts it needs to generate correct marketing copy.

Answer

Lower the temperature to 0.

Answer

Increase the maxTokens to 4000.

Answer

Add a stop sequence to limit output.

Question 2

Your company is developing an AI-powered document processing solution using Azure AI Document Intelligence. The solution must extract data from scanned PDF forms. The forms are in a custom format not supported by prebuilt models. You have 10,000 labeled forms for training. The solution must be deployed in a region that supports Document Intelligence and must be accessible via a REST API. You need to ensure the solution can process forms with high accuracy. What should you do?

Accepted Answer

Train a custom extraction model using the labeled forms. Azure AI Document Intelligence supports training custom extraction models using labeled forms, which is essential for handling custom form layouts not covered by prebuilt models. With 10,000 labeled forms, you have sufficient data to train a high-accuracy model that extracts specific fields via the REST API, meeting the deployment and accessibility requirements.

Answer

Use Azure AI Language to extract entities from the text

Answer

Use a prebuilt model and map fields manually

Answer

Use the Read model and write custom logic to extract fields

Question 3

Your organization needs to analyze customer call transcripts to extract key insights, including sentiment, issues, and resolution. Which THREE Azure AI Language features should you use?

Accepted Answer

Custom named entity recognition. Sentiment analysis (B) is correct because Azure AI Language's sentiment analysis feature evaluates text and returns sentiment labels and confidence scores, which directly satisfies the requirement to extract sentiment from customer call transcripts. Conversation summarization (C) is correct because it is designed to summarize conversations and extract key information such as issues and resolutions from call transcripts, matching the need to identify issues and resolution outcomes. Custom named entity recognition (A) is correct because it lets you train a model to extract domain-specific entities (for example, product names, issue categories, or resolution codes) from transcripts, which supports extracting key insights beyond generic entities. Key phrase extraction (D) is not marked correct because, while it surfaces main talking points, it does not specifically deliver sentiment, issue, or resolution extraction as required. PII detection (E) is not marked correct because it only identifies and redacts personally identifiable information and does not provide sentiment, issue, or resolution insights.

Answer

Key phrase extraction

Answer

PII detection

Question 4

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.

Answer

Azure AI Custom Vision

Answer

Azure AI Translator

Answer

Azure AI Speech

Question 5

A company uses Azure Content Moderator to moderate text in a chat application. They want to automatically reject messages that contain profanity or personal data. Which API should they use?

Accepted Answer

Text Moderation API. The Text Moderation API (D) is the correct choice because it is specifically designed to scan text content for profanity, personally identifiable information (PII), and other unwanted text patterns. This API returns a moderation score and a list of detected terms, enabling automated rejection of messages that violate the defined policies.

Answer

Review API

Answer

Video Moderation API

Answer

Image Moderation API

Question 6

A company uses Azure AI Language Service with Custom Entity Recognition to extract invoice fields. The model correctly extracts invoice numbers but fails to extract dates in the format 'dd/mm/yyyy'. The training data includes dates in 'mm/dd/yyyy' format. What is the most likely issue?

Accepted Answer

The training data does not contain examples with the 'dd/mm/yyyy' format. Custom Entity Recognition in Azure AI Language Service learns patterns from labeled training data. Since the training data only contains dates in 'mm/dd/yyyy' format, the model has not seen any examples of 'dd/mm/yyyy' and therefore cannot generalize to that format. The model relies on the exact token sequences and date structures present in the training set, so missing format variations directly cause extraction failures.

Answer

The dates exceed the maximum entity length

Answer

The language detection is incorrectly identifying the locale

Answer

The model is overfitting to invoice numbers

Question 7

Refer to the exhibit. You are deploying an Azure AI Services resource using an ARM template. After deployment, you cannot access the resource from any client, including the Azure portal. What is the most likely cause?

Accepted Answer

The networkAcls defaultAction is set to Deny with no allowed IP or virtual network rules.. The networkAcls defaultAction set to Deny with no allowed IP or virtual network rules blocks all traffic to the Azure AI Services resource, including requests from the Azure portal and any client. This is because the default network access control list (ACL) denies all traffic unless explicitly permitted by IP rules or virtual network rules, rendering the resource inaccessible even for management operations.

Answer

The SKU S0 does not support network restrictions.

Answer

The cognitiveServiceName conflicts with an existing resource.

Answer

The virtualNetworkRules array is empty.

Question 8

A healthcare organization is building a clinical decision support system that must extract medical entities (e.g., symptoms, diagnoses, medications) from unstructured clinical notes. The solution must be able to detect relationships between entities, such as 'medication X treats symptom Y'. Which Azure AI service should be used?

Accepted Answer

Azure AI Language - Custom NER with entity linking. Azure AI Language's Custom Named Entity Recognition (NER) with entity linking allows training a model to extract domain-specific medical entities such as symptoms, diagnoses, and medications from unstructured clinical notes. Entity linking connects these entities to a knowledge base (e.g., UMLS), which contains structured relationships between medical concepts, enabling the inference of relationships like 'medication X treats symptom Y'. Thus, Custom NER with entity linking is the appropriate service for both entity extraction and relationship detection.

Answer

Azure AI Translator

Answer

Azure AI Speech-to-Text

Answer

Azure AI Document Intelligence (formerly Form Recognizer)

Question 9

Which TWO actions should you take to ensure that a generative AI model deployed on Azure Machine Learning is compliant with data privacy regulations?

Accepted Answer

Implement data masking during preprocessing.. Options A and C are correct. A: Data masking during preprocessing helps anonymize sensitive data before it is used, reducing privacy risks. C: Differential privacy adds noise to the training process, preventing the model from memorizing individual data points. B is wrong because storing data in a separate Azure region does not inherently address privacy compliance; it may help with data residency but not the core privacy protection. D is wrong because encrypting the model at rest with Azure Key Vault is a security measure, not a privacy compliance measure. E is wrong because logging raw input data to Azure Monitor could expose sensitive information, violating privacy.

Answer

Store all training data in a separate Azure region.

Answer

Encrypt the model at rest using Azure Key Vault.

Answer

Log all raw input data to Azure Monitor for auditing.

Question 10

A company uses Azure Computer Vision to moderate user-generated content. The solution must detect adult content and flag it. Which API should you call?

Accepted Answer

Analyze API with visualFeatures set to 'Adult'. The Analyze API with the visualFeatures parameter set to 'Adult' is the correct choice because Azure Computer Vision's Analyze Image operation includes an 'Adult' category that specifically detects adult, racy, and gory content in images. This API returns a confidence score (0 to 1) for each category, allowing the solution to flag content based on a threshold. The other APIs do not provide adult content moderation capabilities.

Answer

Read API

Answer

Detect API

Answer

Describe API

Question 11

Which TWO capabilities are provided by the Azure AI Language service?

Accepted Answer

Custom text classification.. Option C (Custom text classification) is correct because Azure AI Language includes a custom text classification feature that lets you train models to categorize documents or text into user-defined classes. Option E (Key phrase extraction) is correct because Azure AI Language provides prebuilt key phrase extraction to identify the main talking points in unstructured text. Option A (Text translation) is not part of Azure AI Language; translation is handled by Azure AI Translator. Option B (Speech-to-text conversion) belongs to Azure AI Speech, not Azure AI Language. Option D (Image captioning) is a computer vision capability in Azure AI Vision, not Azure AI Language.

Answer

Text translation.

Answer

Speech-to-text conversion.

Answer

Image captioning.

Question 12

You are building a knowledge mining solution for legal documents stored in Azure Blob Storage. The solution must extract entities, key phrases, and relationships from the documents. Which Azure AI service should you use?

Accepted Answer

Azure AI Language. Azure AI Language provides pre-built capabilities for entity extraction, key phrase extraction, and relationship extraction from text. This service includes features like Named Entity Recognition (NER), key phrase extraction, and document analysis that directly meet the requirements for extracting entities, key phrases, and relationships from legal documents. The other options lack one or more of these specific text analytics capabilities.

Answer

Azure AI Document Intelligence

Answer

Azure AI Translator

Answer

Azure AI Search

Question 13

A company uses Azure Content Moderator to moderate user-generated content. They need to ensure that content moderation workflows comply with regional regulations. Which TWO actions should they take?

Accepted Answer

Deploy Content Moderator resources in the required geographic regions to meet data residency requirements.. Deploying Azure Content Moderator resources in the required geographic regions ensures that user-generated content is processed and stored within specific data boundaries, directly addressing data residency regulations. This is a fundamental compliance requirement because Azure resources are region-bound, and data does not leave the selected region unless explicitly configured otherwise.

Answer

Use the free tier to reduce costs while meeting compliance needs.

Answer

Enable geo-tagging on the Content Moderator API to automatically apply region-specific moderation.

Answer

Configure the API to automatically reject any content that violates regional laws.

Question 14

Which THREE factors should be considered when choosing between Azure Computer Vision and Azure Custom Vision? (Choose three.)

Accepted Answer

The need for custom model retraining over time.. Azure Custom Vision is specifically designed for scenarios where you need to retrain a model over time with new labeled data, such as when the visual characteristics of objects change (e.g., new product packaging). Azure Computer Vision is a pre-trained API that cannot be retrained; it only supports fixed, generic models. Custom Vision allows iterative training with your own images, making it essential when model drift or evolving requirements demand periodic retraining.

Answer

Whether the solution runs on edge devices.

Answer

The geographic region of the Azure subscription.

Question 15

Which THREE Azure AI services can be used to extract text from images?

Accepted Answer

Azure AI Search. Option B (Azure AI Search) is correct because it includes AI enrichment with the OCR cognitive skill, which extracts text from image files (e.g., JPEG, PNG) during the indexing pipeline, making the text searchable. Option C (Azure AI Document Intelligence layout model) is correct because the layout model performs OCR on documents and images, extracting printed and handwritten text along with tables and structure from forms and files. Option D (Azure AI Vision OCR) is correct because the Read/OCR API in Azure AI Vision extracts printed and handwritten text from images and documents. Option A (Azure AI Speech) is incorrect because it handles speech-to-text, text-to-speech, and translation of audio, not text extraction from images. Option E (Azure AI Language custom NER) is incorrect because it extracts named entities from existing text, not text from images.

Answer

Azure AI Speech

Answer

Azure AI Language custom NER