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Microsoft AI-103 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement text and speech analysis solutions | 10–15% | - Implement natural language processing
|
| Implement generative AI and agentic solutions | 30–35% | - Build generative AI applications
|
| Implement information extraction and knowledge mining | 10–15% | - Build knowledge bases and search solutions
|
| Plan and manage Azure AI solutions | 25–30% | - Manage AI solution development lifecycle
|
| Implement computer vision solutions | 10–15% | - Build multimodal solutions
|
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
You have a factory that contains a production line.
You need to develop a solution that will analyze a video feed to detect and track the movement of employees as they work on the production line.
Which service should you include in the solution?
- A. Azure Vision in Foundry Tools Spatial Analysis
- B. Azure AI Video Indexer
- C. Azure Vision in Foundry Tools Image Analysis
- D. Azure AI Face
Correct Answer: A 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
Hotspot Question
You have a Microsoft Foundry project that contains a customer support application.
You create an evaluation named Run1 that has the following configurations:
- Includes risk and safety metrics
- Includes the protected material evaluation
- Includes harmful content metrics that use a medium severity threshold You create an evaluation named Run2 that has the following configurations:
- Includes risk and safety metrics
- Includes the protected material evaluation
- Includes harmful content metrics that use a high severity threshold
You run both evaluations against a dataset named DB1 and receive the following results:
- Content harm defect rate of Run1: 12%
- Content harm defect rate of Run2: 4%
- Protected material evaluation of Run1: 6%
- Protected material evaluation of Run1: 6%
You start a fine-tuning job by using DB1. The job fails during automatic RAI checks for multiple content harm types.
You discover that the content filtering configuration is set to high severity.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: No
Changing the content filtering configuration to low severity will not resolve the fine-tuning job issues.
Box 2: Yes
The difference between a 12% defect rate in Run1 and a 4% defect rate in Run2 is entirely consistent with the different severity thresholds configured for the two evaluations.
Box 3: Yes
The protected material evaluation metric is entirely unaffected by changes to the content harm severity threshold.
Reference:
https://learn.microsoft.com/en-us/python/api/azure-ai-evaluation/azure.ai.evaluation
You are building a chatbot.
You need to ensure that the chatbot can classify user input into separate categories. The categories must be dynamic and defined at the time of inference.
Which service should you use to classify the input?
- A. Azure AI Language custom named entity recognition (NER)
- B. Azure AI Language custom text classification
- C. Azure OpenAI text summarization
- D. Azure OpenAI text classification
Correct Answer: D 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
Hotspot Question
You have a Microsoft Foundry project that contains a customer support agent built by using the Foundry Agent Service.
The agent uploads user-provided screenshots to Azure Storage through a ticketing tool and receives a blob URL for additional reasoning.
You need to use image moderation during agent runs and prevent harmful content from being returned during runs. Azure AI Content Safety must access the images by using the blob URL.
The solution must follow the principle of least privilege.
What should you configure for Content Safety? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
You have an Azure AI agent solution.
You plan to create an agent-based app named App1 that will analyze and summarize data for users and generate data-driven recommendations. App1 will be used by non-technical business users and must adapt to new and unforeseen business challenges and improve its performance over time.
You need to identity which type of agent to use in App1. The solution must meet the following requirements:
- Adapt and improve the agents' performance over time based on user
feedback.
- Provide tailored recommendations to help users make informed
decisions.
- Provide the best possible performance of the app.
Which agent type should you identify?
- A. autonomous
- B. cognitive
- C. task automation
- D. prompt-and-response
Correct Answer: B 🗳️
Explanation: Only visible for Lead2Passed members. You can sign-up / login (it's free).
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