510 questions total · 7pages · All types, answers revealed
Which TWO of the following are valid ways to authenticate to the Document Intelligence service?
Standard authentication method.
Why this answer
Authentication is primarily handled through an API key or Microsoft Entra ID (RBAC).
An agent is designed to summarize meeting transcripts but keeps including internal meeting notes in the final summary. What is the most effective way to address this?
Instructional refinement is the best tool for controlling the scope of the model's summary.
Why this answer
Modifying the system prompt to explicitly define the inclusion/exclusion criteria for the summary is the most effective way to control agent output.
You are implementing a RAG pipeline where documents are chunked before embedding generation. You notice that semantic sentences are frequently split across chunk boundaries, resulting in degraded retrieval quality. Which chunking strategy should you implement to resolve this?
Token overlap ensures adjacent chunks share boundary context, preventing semantic fragmentation.
Why this answer
Semantic chunking or sliding window chunking with overlap ensures that context spanning sentence boundaries is preserved across adjacent chunks.
You are implementing a disaster recovery strategy for a critical image processing application that relies on Azure AI Vision. If the primary Azure region experiences an outage, how should you configure failover?
Multi-region deployment with application-level failover or Traffic Manager ensures high availability.
Why this answer
Deploying a secondary Azure AI Vision resource in a paired region and updating the application configuration (or using Azure Front Door / Traffic Manager) enables regional failover.
You are implementing Retrieval-Augmented Generation (RAG) using Azure AI Search as the retriever and Azure OpenAI as the generator. Users report that the generated responses frequently miss critical context located in the middle of long retrieved documents. Which grounding optimization technique should you apply?
Language models tend to pay more attention to information at the beginning and end of a long context window.
Why this answer
Lost-in-the-middle phenomena can be mitigated by placing the most relevant retrieved chunks at the beginning or end of the prompt context, or by employing ranker reordering strategies.
When planning the model selection and versioning lifecycle for Azure OpenAI deployments in an enterprise environment, which TWO practices should you follow? (Choose two.)
Tracking deprecation schedules prevents service disruptions when older model versions are retired.
Why this answer
Best practices include testing model updates in non-production environments first and reviewing deprecation schedules for model versions.
You are evaluating a generative AI application in Azure AI Foundry using automated metrics. You need to measure how well the generated answers are supported by the retrieved source documents. Which evaluation metric should you use?
Groundedness evaluates whether the model response is faithful to the retrieved context.
Why this answer
Groundedness measures the extent to which the generated text is derived solely from the provided source context, preventing hallucinations.
You need to secure communications between an Azure App Service hosting your web app and an Azure AI Computer Vision service. The web app must authenticate to Computer Vision without storing API keys in application settings. Which feature should you enable?
Managed identity removes stored credentials by utilizing Entra ID authentication securely.
Why this answer
A system-assigned or user-assigned managed identity allows the App Service to acquire Microsoft Entra tokens to authenticate to Computer Vision securely without embedded keys.
You need to extract text lines, words, bounding polygons, and selection marks (such as radio buttons and checkboxes) from arbitrary documents without training. Which prebuilt model should you invoke?
The Prebuilt Layout model extracts text, selection marks, paragraphs, and table structures from documents.
Why this answer
The Prebuilt Read model extracts text, layout structures, and selection marks across various document types without requiring any custom model training.
You are deploying an Azure OpenAI GPT-4 model in a region experiencing high demand, and you need to guarantee a dedicated throughput level without contending with other tenants. Which deployment type should you select?
Provisioned deployments allocate dedicated capacity measured in Provisioned Throughput Units.
Why this answer
Provisioned Throughput Units (PTUs) provide reserved, guaranteed model throughput for predictable performance and workloads.
You are designing an agentic workflow in Azure AI Foundry that needs to perform multiple tasks sequentially. Which THREE components are essential for defining the orchestration logic?
Prompt flow is the orchestration engine for agentic workflows.
Why this answer
Prompt flows, tool definitions, and control flow nodes are standard in Azure AI Foundry agent orchestration.
You are designing an asynchronous text analysis workflow using the Azure AI Language service to process large volumes of documents (e.g., hundreds of megabytes of text files stored in Azure Blob Storage). Which TWO features support asynchronous batch processing jobs via the /analyze-text/jobs endpoint?
Custom text classification supports asynchronous batch jobs for processing large numbers of documents.
Why this answer
Asynchronous batch operations in Azure AI Language are supported for resource-intensive tasks such as custom classification, custom NER, and abstractive/extractive summarization.
Which TWO components are essential for creating an effective system prompt?
The persona sets the tone and purpose.
Why this answer
An effective system prompt defines the agent's role (persona) and its constraints (rules).
You need to extract key concepts and main ideas from long-form technical support articles using the Azure AI Language service. Which feature should you invoke?
Key phrase extraction pulls out the main talking points from unstructured text.
Why this answer
Key phrase extraction returns a list of strings denoting the main talking points in the input text.
Your development team needs to deploy an Azure AI Language resource that can be accessed from an on-premises datacenter via an ExpressRoute circuit without traversing the public internet. Which Azure feature should you configure?
A Private Endpoint maps the Azure AI service to a private IP in your VNet, facilitating secure hybrid connectivity via ExpressRoute.
Why this answer
Azure Private Endpoint injects a private IP address from a virtual network into the Azure AI resource, allowing secure access over ExpressRoute or VPN.
Which TWO prebuilt models are officially available in Azure AI Document Intelligence for extracting specialized domain data? (Choose TWO)
The US W-2 tax form is a supported prebuilt model.
Why this answer
Azure AI Document Intelligence provides prebuilt models for W-2 tax forms and invoices, among others.
You are configuring an Azure AI Language resource and want to ensure that it can be accessed securely from an Azure Virtual Network (VNet) without traversing the public internet. Which Azure networking feature should you configure?
Private endpoints secure traffic between your VNet and the Azure AI service.
Why this answer
Private endpoints allow you to connect securely to your Azure AI Language resource from a virtual network using private IP addresses.
You are implementing a tool call in a Prompt Flow. The tool needs to interact with an external REST API. What is the recommended way to manage the API credentials securely?
Connections store secrets securely.
Why this answer
Azure AI Foundry Connections securely store secrets for tool access.
A company requires that all AI models be approved by a compliance officer before they are deployed to production. Which feature facilitates this workflow?
Registry tags can be used to track model lifecycle states like 'Approved' or 'Development'.
Why this answer
Azure AI Model Catalog and Registry allow for lineage and approval tracking in enterprise environments.
Your organization is implementing strict network isolation for Azure OpenAI. Direct internet access from worker nodes is prohibited. Which THREE mechanisms must be correctly configured to allow secure communication? Each correct answer presents part of the solution.
Disabling public network access ensures traffic cannot bypass the private endpoint.
Why this answer
Private endpoint, private DNS zone, and disabling public access ensure secure network isolation.
You need to optimize the retrieval performance of your RAG agent. You find that the search engine returns too many irrelevant documents. What should you adjust?
Hybrid search improves precision by combining semantic relevance with keyword matching.
Why this answer
Hybrid search (combining vector and keyword search) and adjusting ranking parameters can significantly improve retrieval accuracy.
You are implementing a RAG solution where documents contain complex hierarchical headings. To ensure search chunks retain sufficient context about which section they belong to, what chunking strategy should you adopt?
Parent-child chunking links small child chunks to larger parent chunks or headers, maintaining context during retrieval.
Why this answer
Hierarchical chunking or parent-child chunking retains parent section headings and metadata within smaller searchable child chunks, preserving document context.
When establishing a governance strategy for Azure AI resources across multiple cloud teams, which THREE administrative tasks should an administrator perform? (Choose three.)
Least privilege ensures users only have access necessary for their tasks.
Why this answer
Governance involves applying Azure Policies, assigning least-privilege RBAC roles, and organizing resources into management groups and subscriptions.
Your team needs to receive an email alert if the error rate for your AI endpoint exceeds 5% for more than 15 minutes. What should you create?
Alert rules track metric thresholds and action groups define how to notify stakeholders.
Why this answer
Azure Monitor Alert rules allow you to trigger actions (like email notifications via action groups) based on metric thresholds.
You are integrating Azure AI Search with Azure OpenAI for grounded chat generation. Users report that the generated answers are accurate, but the citations returned to the user point to raw internal file paths rather than user-friendly web URLs. How should you resolve this?
Mapping internal storage paths to user-facing URLs in index metadata allows your application to render clean citation links.
Why this answer
Mapping internal file path fields to public URL fields in the Azure AI Search index mapping configuration ensures correct citation links are returned.
You are building a RAG application where documents are updated frequently. You need to ensure that the Azure AI Search index reflects document deletions and updates in near real-time without performing full re-indexing. How should you design the ingestion pipeline?
Indexers support change tracking to automatically add, update, or delete index documents based on source data changes.
Why this answer
Using incremental indexers with change tracking (such as integrated data change detection or custom push APIs with soft-delete metadata) allows efficient updates.
Your company wants to track and allocate Azure AI service costs by department. Which TWO mechanisms can assist with this requirement? (Choose two.)
Cost allocation rules and filters enable accurate department chargeback reporting.
Why this answer
Resource tags and Azure Cost Management filters/chargeback reports are the standard tools for department-level cost allocation.
You are using Document Intelligence to classify documents into different types (e.g., invoices, bank statements). Which model is most appropriate?
Classification models identify document types.
Why this answer
The 'custom classification' model is designed to group documents into predefined categories.
Which TWO factors directly influence the embedding quality and retrieval relevance in an Azure AI Search vector retrieval pipeline? (Choose two.)
The embedding model determines how accurately semantic meaning is captured in vector space.
Why this answer
Embedding model choice and chunking strategy are primary determinants of vector retrieval quality.
You are troubleshooting a Prompt Flow and suspect the issue lies in the input processing. Which THREE tools or techniques can you use?
Breakpoints allow for inspecting flow state.
Why this answer
Debugging in Prompt Flow involves visual inspection of node inputs/outputs, tracing, and log analysis.
You are configuring an agent in Azure AI Agent Service that needs to utilize tools. Which TWO types of tools are natively supported by Azure AI Agent Service? (Choose TWO)
Function calling allows agents to invoke custom APIs and functions.
Why this answer
Code interpreter and Function calling (custom tools) are natively supported built-in tools within Azure AI Agent Service.
You are using an Azure AI model that supports versioning. You want to perform an A/B test by routing 10% of traffic to a new version. Where do you configure this?
The endpoint's traffic settings allow you to allocate percentages to different deployment versions.
Why this answer
In Azure AI managed endpoints, you can define traffic distribution across multiple deployments within the same endpoint.
Your company processes business cards from international clients. Which prebuilt Azure AI Document Intelligence model should you use to extract names, company names, emails, and phone numbers from these cards?
This model is specifically trained for business cards.
Why this answer
The prebuilt business card model (prebuilt-businessCard) extracts contact information from business cards.
You are implementing Retrieval-Augmented Generation (RAG) in Azure AI Foundry using Azure AI Search as the grounding data source. Which indexing feature should you enable to ensure the system can perform semantic ranking alongside traditional keyword search?
Enabling semantic search adds semantic ranking capabilities to your Azure AI Search index, which is recommended for RAG scenarios.
Why this answer
Semantic ranking uses advanced language models to re-rank top search results, significantly improving the relevance of retrieved chunks for RAG pipelines.
As part of responsible AI practices in Azure AI Foundry, which TWO actions should you perform to evaluate and mitigate model fairness and safety risks before deployment? (Choose two)
Automated evaluation tools in Azure AI Foundry help quantify model performance and safety metrics against validation datasets.
Why this answer
Evaluating models using automated evaluation metrics (such as groundedness and relevance) and conducting red teaming are essential responsible AI practices.
You are deploying an Azure AI Speech resource. Your compliance team stipulates that all data sent to the speech service must be processed strictly within the geographical boundaries of the European Union and must not be used for Microsoft's model training. How should you ensure this compliance?
Deploying in an EU region ensures regional data processing, and Microsoft's enterprise terms guarantee customer data is not used to train base models.
Why this answer
Azure AI Services comply with regional data residency and offer data privacy controls ensuring customer data is stored at rest in the specified region and not used for training without explicit opt-in.
You are managing a multi-tenant SaaS application that uses Azure AI Vision. Each tenant has their own isolated data, and you want to track costs per tenant. How should you provision Azure AI services to achieve granular cost attribution?
Dedicated resources per tenant provide exact, isolated cost tracking via Azure Cost Management.
Why this answer
Provisioning separate Azure AI Services resources per tenant (or using resource tags with Azure Cost Management) allows granular cost tracking, though separate resources provide strict billing isolation.
You are using Custom Vision and want to programmatically publish a trained iteration so that prediction endpoints can use it. Which API operation should you call?
This is the correct endpoint for publishing a training iteration.
Why this answer
Publishing an iteration in Custom Vision requires calling the publish iteration endpoint with the published name and prediction resource ID.
Your enterprise requires strict security and governance over your Azure AI Vision resources. Which THREE security configurations should you implement? (Choose three.)
Private endpoints keep traffic off the public internet.
Why this answer
Enterprise security for Azure AI Services includes Private Endpoints, disabling local authentication in favor of Microsoft Entra ID (RBAC), and Key Vault integration for secrets.
You are configuring a Custom Vision project to classify images of plant diseases. You notice that some image files uploaded via the API are rejected because they exceed the maximum allowed file size. What is the maximum image file size supported by Custom Vision for training?
Custom Vision imposes a 6 MB limit per image for training data uploads.
Why this answer
Custom Vision training images uploaded via API or portal generally have a maximum file size limit of 6 MB per image.
You are provisioning an Azure AI services account and want to ensure that all telemetry and monitoring metrics are collected. Which built-in monitoring feature is automatically enabled on Azure AI resources without requiring additional agent installation?
Platform metrics (such as Total Calls, Latency, and Failed Requests) are collected automatically by Azure Monitor for PaaS resources.
Why this answer
Azure Monitor platform metrics are collected automatically for all Azure PaaS resources without installing agents.
You are developing a mobile application that captures business card photos and extracts contact information. Which Azure AI Vision feature is specifically designed to extract printed and handwritten text lines and words?
The Read feature extracts text lines, words, bounding boxes, and confidence scores.
Why this answer
The Read feature is Azure AI Vision's optical character recognition (OCR) tool for extracting printed and handwritten text.
You are designing a secure, production-grade architecture for an Azure AI Search service integrated with Azure OpenAI. Which THREE security and operational best practices should you implement? Each correct answer presents part of the solution.
Diagnostic logging provides visibility into query latency, errors, and performance bottlenecks.
Why this answer
Managed identities, private endpoints, and monitoring metrics are essential best practices.
You are testing a Custom Vision object detection model using the test image feature in the portal. You notice that objects are detected with low confidence scores. You want to improve the model's performance without adding more training images. What can you adjust in the training settings?
Increasing the training time allows the underlying neural network more epochs to converge on complex patterns.
Why this answer
While training data is primary, training iterations allow selecting different training time budgets or domains, but adjusting the probability threshold in prediction evaluation helps filter results. However, re-training with advanced training time settings can improve model accuracy.
Your enterprise team is deploying multiple Azure AI Custom Vision resources across different development stages (Dev, Test, Prod). You need to ensure that billing costs for the Dev environment are billed to a specific cost center. Which Azure feature should you use to categorize these costs?
Tags apply key-value metadata to resources, which can then be grouped and analyzed in Azure Cost Management.
Why this answer
Azure resource tags allow categorizing resources for cost allocation and management reporting.
You need to retrieve coordinates of people detected in an image using Azure AI Vision 4.0. Which visual feature should you request?
The people feature returns bounding box coordinates for humans in the image.
Why this answer
The 'people' visual feature detects people in the image and returns their bounding box coordinates.
You are configuring an Azure AI Document Intelligence orchestration model to automatically classify and extract data from incoming customer correspondence, which includes invoices, work orders, and purchase orders. One of the component models is failing to classify documents correctly. How should you resolve this issue?
Improving the classification accuracy of an orchestration model requires improving the distinctiveness and quality of the underlying component custom models.
Why this answer
Orchestration models rely on component custom models. If classification fails, you must retrain or refine the specific component model with distinct training samples.
You are building an agentic workflow in Microsoft Foundry using Semantic Kernel. The agent needs to call an external enterprise API to retrieve customer billing data. The API requires OAuth 2.0 user-delegated tokens. How should you configure the plugin registration to securely pass the user context?
Mapping the authorization header dynamically ensures user-delegated tokens are forwarded correctly.
Why this answer
User-delegated authentication in Semantic Kernel plugins requires leveraging the active turn context to propagate the user's OAuth 2.0 token through the kernel invocation pipeline.
You are designing a generative AI application in Azure AI Foundry that supports multi-turn conversations with memory. Which THREE components are required to properly maintain conversational state and context? (Choose THREE)
Threads store the ongoing conversation history so the model remembers prior turns.
Why this answer
Agent threads/session storage, message history management, and context window truncation or summarization strategies are required for multi-turn conversational memory.
You are designing a secure RAG retrieval pipeline in Azure AI Search. Which THREE indexing or search configurations are essential when handling confidential documents? (Choose THREE)
CMK ensures search indexes are encrypted with keys managed in Azure Key Vault.
Why this answer
Security trimming (filters), encrypted indexes, and restricted network access via private endpoints are essential for confidential RAG pipelines.
Your team needs to extract data from a large volume of standardized tax forms using Azure AI Document Intelligence. The forms have a fixed layout where fields are always in the exact same location. Which model type provides the fastest training and highest accuracy for this specific use case?
Custom template models excel at extracting data from forms with consistent, fixed layouts.
Why this answer
Custom template models are optimized for forms with consistent visual structures and fixed layouts, requiring fewer training documents and providing high accuracy.
What is the purpose of 'Batch Inference' in Azure AI Foundry?
Batch inference is ideal for large-scale evaluation and processing.
Why this answer
Batch inference allows you to process large volumes of data offline, which is more cost-effective and efficient than real-time requests.
You are monitoring the performance of a deployed Azure OpenAI model. You notice occasional HTTP 429 (Too Many Requests) errors occurring during peak traffic hours. Which monitoring and management action should you take to resolve this issue?
HTTP 429 errors are rate-limit violations best addressed by monitoring usage metrics and increasing provisioned throughput.
Why this answer
HTTP 429 errors indicate that you have exceeded the rate limits (Tokens Per Minute or Requests Per Minute) of your provisioned tier. Upgrading to a Provisioned Throughput deployment or implementing exponential backoff retry logic resolves rate-limiting errors.
Which THREE of the following are components of a standard Prompt Flow DAG (Directed Acyclic Graph)?
Flows require input definitions.
Why this answer
Inputs, Tools (Nodes), and Outputs are fundamental to Prompt Flow structure.
When planning an Azure AI solution deployment strategy, what are THREE key considerations for model versioning and lifecycle management? (Choose three.)
Regression testing ensures that new model versions do not negatively impact application outputs.
Why this answer
Model updates require planning around version deprecation notices, validating output consistency, and testing rollback strategies. Relying on auto-updates without testing can break downstream integrations.
You are troubleshooting a low confidence score on specific fields extracted by your Azure AI Document Intelligence custom template model. Which TWO actions can help improve the extraction confidence for those fields? (Choose TWO)
High-quality training images improve OCR accuracy and subsequent field extraction confidence.
Why this answer
Improving training quality through diverse, high-quality samples and accurate labeling improves confidence scores.
You are deploying a custom model to an Azure AI managed endpoint. You need to ensure the deployment can access a Key Vault secret without storing credentials in the deployment configuration. What should you do?
Managed identities allow Azure resources to authenticate to Key Vault without storing secrets.
Why this answer
Using a User-assigned managed identity allows the endpoint to authenticate to other Azure services like Key Vault securely.
You are deploying an LLM in Azure AI Foundry and need to monitor for toxicity and jailbreak attempts in real-time. Which feature should you enable?
Content Safety provides built-in filters for jailbreak and toxicity detection.
Why this answer
Azure AI Content Safety is the integrated service for monitoring model inputs and outputs for harmful content.
You have an Azure AI endpoint exposed to the internet. You want to ensure traffic is inspected for malicious patterns. What is the recommended service?
WAF inspects incoming web traffic to block malicious attacks.
Why this answer
Azure Web Application Firewall (WAF) provides protection against common web vulnerabilities like SQL injection and cross-site scripting.
When setting up an Azure AI service, you choose the 'Standard' tier. What is the primary benefit of this compared to the 'Free' tier?
Standard tier is designed for production with higher limits and availability guarantees.
Why this answer
Standard tiers provide higher capacity, production-level SLAs, and support for enterprise-grade features.
You are orchestrating a multi-agent system in Microsoft Foundry where Agent A generates code and Agent B reviews it. Agent B frequently gets stuck in a loop trying to optimize minor syntax formatting. How should you design the agentic workflow to prevent this infinite refinement loop?
Explicit termination conditions and state management are essential pattern controls in multi-agent orchestration.
Why this answer
Establishing a strict iteration limit or state machine check within the orchestrator prevents agents from looping indefinitely.
Your organization requires that all Azure AI Vision API calls are audited and that request payloads (including images) are logged for compliance investigations. Which Azure service feature should you configure alongside Azure AI Services?
Diagnostic settings capture service logs, metrics, and audit information for security and compliance monitoring.
Why this answer
Azure Diagnostic Settings allow logging API requests, metrics, and audit trails to Azure Monitor, Log Analytics, or Azure Storage.
You are integrating Azure AI Vision Read API into a high-throughput workflow. You receive an HTTP 202 Accepted response. What action should your application take next?
Asynchronous OCR operations require polling the Operation-Location endpoint.
Why this answer
An HTTP 202 response indicates the asynchronous operation has started. The application must poll the URL provided in the Operation-Location header.
You are configuring custom named entity recognition in Language Studio. Which TWO types of entity components can you configure when defining custom entities? (Choose two.)
Regex components allow pattern-based entity extraction.
Why this answer
Custom NER projects support Learned entity components (trained from labeled data) and Regex or List components for exact pattern or dictionary matching.
You are evaluating an agentic workflow in Azure AI Foundry that performs multi-step reasoning. The agent occasionally enters an infinite loop, repeatedly calling the same tool with identical arguments. Which architectural pattern or configuration should you apply to prevent this behavior?
Setting a max iteration threshold halts execution if the agent exceeds expected reasoning steps, preventing infinite loops.
Why this answer
Implementing agent execution limits, such as maximum iteration counters or step limits within the orchestration loop, prevents agents from falling into infinite tool-calling loops.
You are optimizing performance for a real-time video analytics pipeline that sends video frames to Azure AI Vision. Due to network bandwidth constraints, you need to reduce payload sizes while maintaining high OCR accuracy. What is the recommended approach?
Optimized JPEG encoding and careful resolution scaling reduce payload bandwidth while preserving text fidelity.
Why this answer
Compressing frames as high-quality JPEGs or WebP images and resizing them to fit optimal dimension thresholds without excessive downsampling preserves OCR accuracy while drastically reducing payload size.
You are implementing a multi-turn conversational agent in Azure AI Foundry. As the conversation grows longer, API latency and costs increase significantly. Which strategy should you implement to manage the conversation history effectively?
Summarizing historical turns preserves context while drastically reducing token consumption.
Why this answer
Summarizing older conversation turns or maintaining a sliding window of recent messages keeps token counts manageable.
Which Azure AI service should you use if you need to train a model to recognize your company's proprietary product packaging using custom-labeled images with minimal machine learning expertise?
Custom Vision is designed for training custom image classifiers and object detectors with user-provided images.
Why this answer
Custom Vision allows users to train custom image classifiers and object detectors using a web portal with no ML expertise required.
You are designing an enterprise RAG solution using Azure AI Search and Azure OpenAI. You need to ensure data security and compliance across different user permission tiers. Which TWO actions should you implement? (Choose two.)
Encryption in transit is a core security requirement for enterprise compliance.
Why this answer
Security trimming in Azure AI Search ensures users only retrieve documents they have access to, and encrypted connections protect data in transit.
You need to restrict access to an Azure AI Custom Vision training resource so that only members of a specific Azure AD security group can manage projects and train models. How should you configure access control?
Assigning RBAC roles to security groups grants the precise permissions needed for resource management.
Why this answer
Role-Based Access Control (RBAC) allows assigning built-in or custom roles like Cognitive Services Contributor to specific Azure AD security groups at the resource scope.
You are building a custom text classification solution using Azure AI Language in Language Studio. You have a dataset where each document can belong to multiple categories simultaneously (e.g., a news article can be tagged as both 'Technology' and 'Finance'). What classification type should you configure?
Multi-label classification is designed for scenarios where a single document can be assigned multiple overlapping categories.
Why this answer
Multi-label classification allows a document to be associated with zero, one, or multiple classes simultaneously, whereas single-label classification restricts each document to exactly one class.
An invalid project ID returns a 400 Bad Request indicating the project cannot be found.
Why this answer
The project ID GUID provided in the URL path is malformed, does not exist, or belongs to a different region/resource.
Which HTTP status code does the Azure AI Vision Read API return upon successfully initiating an asynchronous OCR analysis job?
HTTP 202 is returned for accepted asynchronous long-running operations.
Why this answer
Asynchronous operations in Azure AI Services return HTTP 202 Accepted when the request has been accepted for processing.
You are implementing responsible AI practices in Azure AI Foundry for a public-facing chatbot. Which THREE safety evaluations or controls should you implement to protect users and the organization? (Choose THREE)
Protected material detection identifies if the model generates copyrighted text or source code verbatim.
Why this answer
Protected material detection, content safety filtering for harmful categories, and jailbreak/prompt shielding defenses are core responsible AI controls in Azure AI.
You are troubleshooting a multi-agent workflow in Azure AI Foundry where an agent fails to invoke an external API tool correctly. Which THREE debugging steps should you perform? (Choose THREE)
Verifying connectivity and auth ensures network blocks or expired credentials are not failing the call.
Why this answer
Inspecting tool definition JSON schemas, reviewing model output tool call arguments, and verifying API endpoint connectivity are key troubleshooting steps.
Practice AI-103 by domain
Target a specific domain to shore up weak areas.