AI-102 Multiple Select — 20 Questions

Question 1

You are building a custom question answering solution using Azure AI Language. Which TWO actions are required to deploy the solution?

Accepted Answer

Create a Custom Question Answering project in Azure AI Language.. A Custom Question Answering project is the container for your question-answer pairs, synonyms, and active learning settings within Azure AI Language. You must create this project to define the knowledge base that the solution will query against.

Answer

Train a custom model using the Azure AI Language training API.

Answer

Create a QnA Maker service in the Azure portal.

Answer

Publish the project to a web app bot.

Question 2

You are developing an Azure AI solution that uses pre-built models from Azure AI Vision to analyze images. The solution must be able to detect objects and read printed text. Which TWO capabilities should you use?

Accepted Answer

Object detection. Azure AI Vision's Object Detection capability identifies and locates objects within an image, returning bounding box coordinates and labels. This directly meets the requirement to 'detect objects' in the solution.

Answer

OCR (legacy)

Answer

Facial detection

Answer

Image tagging

Question 3

Which TWO Azure services can be used together with Azure OpenAI to implement a Retrieval-Augmented Generation (RAG) solution?

Accepted Answer

Azure Cosmos DB. Azure Cosmos DB is correct because it can serve as a vector database for storing and querying embeddings generated by Azure OpenAI. When combined with Azure AI Search, which provides hybrid search (vector + keyword) and indexing capabilities, it enables a complete RAG pipeline where relevant documents are retrieved and passed as context to the OpenAI model for grounded generation.

Answer

Azure Blob Storage

Answer

Azure SQL Database

Answer

Azure Functions

Question 4

Which THREE components are required to build a custom chat application using Azure OpenAI Service that can answer questions based on your own private data?

Accepted Answer

The 'Add your data' feature configured in Azure OpenAI Studio.. The 'Add your data' feature in Azure OpenAI Studio provides a no-code interface to connect your private data sources (e.g., Azure Blob Storage, local files) to an Azure OpenAI chat model. It automatically chunks the data, creates an Azure AI Search index, and configures the retrieval-augmented generation (RAG) pipeline, enabling the model to answer questions grounded in your proprietary content without fine-tuning.

Answer

A fine-tuned custom model.

Answer

An Azure OpenAI embeddings model deployment.

Question 5

Which TWO Azure AI services can be used to extract text from images as part of a knowledge mining pipeline?

Accepted Answer

Azure AI Document Intelligence. Azure AI Document Intelligence (formerly Form Recognizer) is correct because it is specifically designed to extract text, tables, and key-value pairs from scanned documents and images using optical character recognition (OCR) and deep learning models. It is a core service for knowledge mining pipelines that require structured data extraction from unstructured documents.

Answer

Azure AI Language

Answer

Azure AI Video Indexer

Answer

Azure AI Custom Vision

Question 6

You are designing a solution that uses Azure AI Document Intelligence to extract data from invoices. The solution must handle high throughput and process documents in batch. Which TWO configuration options should you use?

Accepted Answer

Provision a standard (S0) tier Document Intelligence resource. The standard (S0) tier is required for production-grade throughput because it offers higher transactions per second (TPS) and better scalability compared to the free (F0) tier. For batch processing of invoices, the async document analysis API is the correct choice because it supports submitting multiple documents in a single call and returns results via a polling mechanism, which is designed for high-volume scenarios.

Answer

Use the synchronous API for each invoice

Answer

Train a custom model for invoice extraction

Answer

Store output directly in Azure Blob Storage without API calls

Question 7

You are designing a conversational AI solution using Microsoft Copilot Studio. The solution must: - Allow users to ask questions about company policies stored in SharePoint Online. - Use generative answers with grounding data. - Ensure that responses are based only on approved documents. - Support authentication via Microsoft Entra ID. Which THREE components must be configured as part of the solution?

Accepted Answer

Create a new data source in Copilot Studio pointing to SharePoint Online.. Copilot Studio allows you to create a new data source that connects directly to SharePoint Online, enabling the generative answers feature to retrieve and ground responses on approved policy documents stored there. This ensures that only content from the specified SharePoint site is used, meeting the requirement for grounding data from approved documents.

Answer

Create a Power Automate flow to retrieve documents from SharePoint.

Answer

Train an AI Builder model to classify policy documents.

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

Answer

Personally identifiable information (PII) detection

Question 9

Which THREE considerations are important when planning to use Azure OpenAI Service in a production environment?

Accepted Answer

Configure content filtering to block harmful outputs. Azure OpenAI Service includes built-in content filtering to detect and block harmful outputs such as hate, violence, or self-harm. This is a critical safety and compliance requirement for production deployments, as it helps meet responsible AI principles and regulatory obligations. Without configuring content filters, the service could generate inappropriate responses that violate usage policies or legal standards.

Answer

Train a custom model from scratch using your own data

Answer

Deploy the service within a virtual network (VNet)

Question 10

A legal firm is using Azure AI Language to analyze contracts. They need to extract key clauses, parties involved, and dates. The solution must be customizable to their specific contract types. Which TWO Azure AI Language features should they use?

Accepted Answer

Prebuilt NER for Legal. Prebuilt NER for Legal is correct because it provides out-of-the-box entity extraction tailored to legal documents, including parties, dates, and key clauses, without requiring custom training. This feature is specifically designed for legal use cases, making it ideal for a firm that needs to quickly extract standard legal entities from contracts.

Answer

Conversation summarization

Answer

Key phrase extraction

Answer

Entity linking

Question 11

Which TWO features of Azure AI Content Safety can help you moderate user-generated content in a social media application?

Accepted Answer

Self-harm content detection.. Self-harm content detection (A) is a feature of Azure AI Content Safety that specifically identifies text or images related to self-harm, which is a critical category for moderating user-generated content in social media to prevent harm and comply with safety policies. Hate speech severity detection (B) is another core feature that classifies hate speech into severity levels (e.g., low, medium, high), enabling nuanced moderation of offensive content.

Answer

PII redaction.

Answer

Groundedness detection.

Answer

Prompt injection detection.

Question 12

You are using Azure AI Document Intelligence to extract data from scanned contracts. The contracts contain tables and handwritten signatures. Which TWO features should you enable?

Accepted Answer

Train a custom neural model to recognize handwritten signatures.. Options A and B are correct because a custom neural model can be trained to recognize handwritten signatures (A), and enabling table extraction in the custom model extracts tables from contracts (B). Option C is incorrect because OCR is already enabled by default in Document Intelligence and does not need to be separately enabled. Option D is wrong because form recognition for key-value pairs is not required for this scenario, as the focus is on tables and signatures. Option E is wrong because the prebuilt-layout model does not support custom training for signature recognition and may not handle handwritten elements as accurately as a custom model.

Answer

Enable OCR to read scanned text.

Answer

Use form recognition to capture key-value pairs.

Answer

Use the prebuilt-layout model for all extraction.

Question 13

Which TWO Azure AI services can be used to detect objects in images?

Accepted Answer

Custom Vision. Custom Vision (Option C) is correct because it allows you to train a custom image classification or object detection model using your own labeled images. You can upload images, tag objects with bounding boxes, and then use the trained model to detect specific objects in new images, making it a valid choice for object detection tasks.

Answer

Video Indexer

Answer

Face API

Answer

Azure AI Document Intelligence

Question 14

Which TWO Azure AI services can be used to build a conversational chatbot that uses generative AI? (Choose two.)

Accepted Answer

Azure AI Bot Service. Azure AI Bot Service (B) provides a dedicated platform for building, deploying, and managing conversational chatbots, integrating with channels like Microsoft Teams and Slack. Azure OpenAI Service (E) enables generative AI capabilities by providing access to large language models (e.g., GPT-4) that can generate human-like responses, making it ideal for powering the conversational intelligence of a chatbot.

Answer

Azure AI Search

Answer

Azure AI Translator

Answer

Azure AI Language

Question 15

Which THREE factors should you consider when selecting a region for an Azure AI Language resource?

Accepted Answer

Data residency requirements.. Data residency requirements (Option C) are critical when selecting an Azure region for an AI Language resource because Azure AI Language processes and stores customer data within the region where the resource is provisioned. Many organizations have compliance obligations (e.g., GDPR, HIPAA, or local data sovereignty laws) that mandate data remain within specific geographic boundaries, so choosing a region that aligns with these requirements is essential.

Answer

Pricing differences.

Answer

Availability of the Free tier SKU.

Question 16

Which THREE components are required to build a custom question-answering solution using Azure AI Language Service?

Accepted Answer

A bot channel registration or web app to interact with users. A bot channel registration or web app is the front-end interface that allows users to submit questions and receive answers from the custom QnA solution. Without this interaction layer, the knowledge base cannot be queried by end users, making it an essential component for a complete solution.

Answer

An Azure AI Search index

Answer

An Azure Functions app for serverless compute

Question 17

Which TWO actions should you take when designing an Azure AI solution that uses Microsoft Foundry to ensure responsible AI practices?

Accepted Answer

Implement a human-in-the-loop review for critical decisions. Implementing a human-in-the-loop review provides oversight for critical decisions. Option C is correct because running an AI fairness assessment detects bias. Option B is wrong because optimizing for maximum throughput is about performance, not responsible AI. Option D is wrong because storing all training data indefinitely may violate privacy and is not a recommended practice for responsible AI. Option E is wrong because removing all explainability metrics hinders transparency, which is important for responsible AI.

Answer

Optimize the model for maximum throughput

Answer

Store all training data indefinitely for auditability

Answer

Remove all explainability metrics to simplify the model

Question 18

A company is planning to use Azure AI services. They require the ability to audit all API calls for compliance. Which THREE components should they enable?

Accepted Answer

Azure Monitor. Azure Monitor is correct because it provides a centralized platform for collecting, analyzing, and acting on telemetry data from Azure resources, including API call logs. By enabling diagnostic settings for the AI service, you can route audit logs (such as all REST API requests and responses) to Azure Monitor, which then integrates with Log Analytics for querying and alerting. This triad—Azure Monitor, Log Analytics workspace, and diagnostic settings—forms the complete pipeline required to audit all API calls for compliance.

Answer

Azure RBAC roles for the service

Answer

Managed identity for the service

Question 19

You are deploying an Azure AI solution that uses multiple services. You need to manage access keys securely. Which TWO methods should you use?

Accepted Answer

Use Azure Key Vault to store the keys.. Azure Key Vault is the recommended service for securely storing and managing access keys, secrets, and certificates. By storing AI service keys in Key Vault, you centralize secret management, control access via Azure RBAC, and avoid hardcoding credentials in code or configuration files. This aligns with the principle of least privilege and reduces the risk of accidental exposure.

Answer

Embed the keys directly in application code.

Answer

Store keys in Azure App Configuration.

Answer

Use Key Vault's automatic key rotation feature.

Question 20

Which TWO Azure AI services can be used to extract text from images and PDFs? (Select two.)

Accepted Answer

Azure AI Vision OCR. Azure AI Vision OCR (Optical Character Recognition) is designed to extract printed and handwritten text from images, while Azure AI Document Intelligence (formerly Form Recognizer) specializes in extracting text, tables, and key-value pairs from documents, including PDFs. Both services provide robust text extraction capabilities from visual sources, making them the correct choices.

Answer

Azure AI Translator

Answer

Azure AI Search

Answer

Azure AI Language