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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Analyze visual content
|
| Topic 2: Implement text analysis and information extraction solutions | 10-15% | - Analyze and extract information
|
| Topic 3: Implement generative AI solutions | 25-30% | - Develop generative AI applications
|
| Topic 4: Implement agentic solutions | 20-25% | - Build AI agents
|
| Topic 5: Plan and manage Azure AI solutions | 25-30% | - Manage AI solution lifecycle
|
Question 1
You have a Microsoft Foundry agent that grounds responses from an Azure Search index that contains the following:
- Searchable text fields for product names and product codes
- A vector field that stores embeddings for product descriptions
You need to ensure that users can query the index by using the following:
- Exact product names or codes
- Natural language descriptions of the products
What should you configure?
A. semantic search only
B. keyword search only
C. hybrid search
D. vector search only
Question 2
You are developing a new sales system that will process user-generated video and text from a public-facing website.
You plan to notify users that their data has been processed by the sales system.
Which responsible AI principle does this help meet?
A. reliability and safety
B. transparency
C. fairness
D. inclusiveness
Question 3
You have an application named App1 that uses Azure Speech in Foundry Tools to transcribe live calls.
Transcript segments often contain both English and Spanish. App1 sends each segment to Azure Translator in Foundry Tools to translate to another language.
Sometimes, mixed-language segments result in incomplete or incorrect translations.
You need to reduce translation errors. The solution must ensure that the entire transcript is translated successfully.
What should you do before sending the segments to Translator?
A. Split the mixed-language segments into single-language segments and translate each segment separately.
B. Specify English as the source language in the translation request for all the segments.
C. Use document translation to translate the entire transcript as a single document.
D. Enable automatic language detection for the translation request.
Question 4
Hotspot Question
You have a Microsoft Foundry project that contains an internal Q&A agent.
Users report the following issues when they ask the agent questions:
- An increase in the following response: "No relevant information
found"
- Periodic HTTP 429 rate limit exceeded errors during peak hours
You need to identify whether each issue is caused by model unavailability, resource limits, or inference failures.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Question 5
Drag and Drop Question
You have a Microsoft Foundry project that contains a deployed ticket-triage agent.
You discover that sometimes the agent responds without calling any tools, even when a tool is required.
You need to ensure that the agent calls a tool during execution.
How should you complete the Python code? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Solutions:
| Question 1 Answer: C | Question 2 Answer: B | Question 3 Answer: A | Question 4 Answer: Only visible for members | Question 5 Answer: Only visible for members |
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