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| Section | Weight | Objectives |
|---|---|---|
| Implement computer vision solutions | 10–15% | - Build multimodal solutions
|
| Implement text and speech analysis solutions | 10–15% | - Implement natural language processing
|
| Plan and manage Azure AI solutions | 25–30% | - Manage AI solution development lifecycle
|
| Implement information extraction and knowledge mining | 10–15% | - Build knowledge bases and search solutions
|
| Implement generative AI and agentic solutions | 30–35% | - Design and implement intelligent agents
|
A multimodal agent processes user-uploaded images. An attacker embeds hidden text instructions inside an image, hoping the agent will read and act on them. Which Azure AI Content Safety capability is designed to detect this kind of attack?
Correct Answer: B 🗳️
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You have a Microsoft Foundry project that contains a prompt agent used by a customer support web app.
The agent is invoked from a Python service that does NOT run in the Foundry portal.
You need to implement end-to-end tracing to capture latency breakdowns and exceptions across agent runs.
Which two components can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Correct Answer: B,C 🗳️
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You have a Microsoft Foundry project that ingests scanned PDF invoices stored in Azure Blob Storage. Each invoice contains printed fine items and has a table-based layout.
Extracted results are stored as structured JSON and used as grounding data for an agent in a Retrieval Augmented Generation (RAG) solution.
You need to create a single analyzer that meets the following requirements:
- Extracts the invoice number, invoice date, vendor name, and total
amount across varying templates
- Returns confidence scores so that results with confidence below 0.80
can be routed for supervisor review
What should you use?
Correct Answer: A 🗳️
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You have a custom named entity recognition (NER) project in Azure Language in Foundry Tools for support tickets. The schema for the project contains an entity type named ContactInfo.
In tagged training files, ContactInfo is used for phone numbers, email addresses, and social media handles.
Model evaluation shows low precision for ContactInfo, including false positives in which nearby text is extracted as ContactInfo.
You need to improve the precision of the project.
What should you do before retraining the model?
Correct Answer: C 🗳️
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You are building an app by using the Semantic Kernel.
You need to include complex objects in the prompt templates of the app. The solution must support objects that contain subproperties.
Which two prompt templates can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Correct Answer: C,D 🗳️
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