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Microsoft AI-103 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Analyze visual content
|
| Topic 2: Implement agentic solutions | 20-25% | - Manage agent operations
|
| Topic 3: Plan and manage Azure AI solutions | 25-30% | - Plan Azure AI resources
|
| Topic 4: Implement generative AI solutions | 25-30% | - Develop generative AI applications
|
| Topic 5: Implement text analysis and information extraction solutions | 10-15% | - Analyze and extract information
|
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
A text-to-speech solution frequently pronounces technical terms incorrectly. You need to correct pronunciation while minimizing development effort.
- A. Apply SSML say-as.
- B. Adjust SSML prosody.
- C. Use Whisper.
- D. Use SSML to specify phonemes.
- E. Train a custom neural voice.
Correct Answer: D 🗳️
Explanation: Only visible for DumpsTorrent members. You can sign-up / login (it's free).
You have a Microsoft Foundry project that processes procurement documents submitted by suppliers.
You need to implement two pipelines by using Azure Content Understanding in Foundry Tools. The solution must meet the following requirements:
* Include a pipeline named Pipeline1 that supports cost-effective, high-volume processing of standalone PDF invoices.
* Include a pipeline named Pipeline2 that supports cross-document validation by using multi-step reasoning and reference data.
How should you configure each pipeline? To answer, drag the appropriate configurations to the correct pipelines. Each configuration 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.
Correct Answer:
Explanation:
Pipeline1: Single-file task in standard mode
Pipeline2: Multi-file task in pro mode
Pipeline1 should use a single-file task in standard mode because the workload is high-volume processing of standalone PDF invoices. Azure Content Understanding standard mode is intended for individual files that require straightforward structured extraction, and Microsoft describes it as minimizing cost and latency for broad, data-centric processing scenarios. This makes it the best fit for cost-effective invoice extraction where each PDF can be processed independently.
Pipeline2 should use a multi-file task in pro mode because the requirement includes cross-document validation, multi-step reasoning, and reference data. Microsoft guidance states that pro mode is designed for advanced scenarios requiring multi-step reasoning and cross-file analysis, including processing multiple input files in a single request, validating or enriching data across documents, and using reference data to guide extraction and validation.
Single-file pro mode would add unnecessary capability for Pipeline1 and would not optimize for cost- effective high-volume standalone processing. Multi-file standard mode does not meet the pro-mode requirement for reference-data-based reasoning. Reference topics: Azure Content Understanding standard mode, pro mode, single-file tasks, multi-file tasks, field extraction, and procurement document validation.
You have 10,000 ASCII files and need to identify files containing specific phrases by using cosine similarity.
- A. GPT-4
- B. GPT-4-32k
- C. GPT-35 Turbo
- D. text-embedding-ada-002
Correct Answer: D 🗳️
Explanation: Only visible for DumpsTorrent members. You can sign-up / login (it's free).
You have a Microsoft Foundry project that contains an agent. The agent has a Model Context Protocol (MCP) tool that queries a knowledge base stored in Azure AI Search.
Some agent runs return answers from the base model without invoking the knowledge base, which results in responses without grounded citations.
You are provided with the following code snippet that runs the agent.
run = project_client.agents.runs.create_and_process(
thread_id=thread.id,
agent_id=agent.id,
)
You need to add the correct tool_choice parameter to the code to deterministically force the agent to invoke the MCP tool on each run.
What should you add?
- A. tool_choice={ " required " }
- B. tool_choice={ " auto " }
- C. tool_choice ={ " type " : " mcp " }
- D. tool_choice={ " type " : " knowledge_base " }
Correct Answer: A 🗳️
Explanation: Only visible for DumpsTorrent members. You can sign-up / login (it's free).
You have a Microsoft Foundry project that contains an agent. The agent uses two tools to perform the following actions:
* Use Azure AI Search to retrieve answers from a private product documentation index.
* Use the web search tool to retrieve public information on the internet.
You need to ensure that for a specific run, the agent deterministically retrieves information only from the internet. To what should you set tool_choice?
- A. " auto "
- B. " required "
- C. { " type " : " bing_grounding " }
- D. { " type " : " azure_ai_search " }
Correct Answer: C 🗳️
Explanation: Only visible for DumpsTorrent members. You can sign-up / login (it's free).
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