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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. You build a chatbot that uses the Azure OpenAI GPT-4 model to generate song lyrics.
You need to ensure that responses do NOT contain lyrics from popular songs that might have been ingested during model training.
Which Azure AI Content Safety API should you use?

A) Groundedness detection
B) Custom categories
C) Analyze Text
D) Protected material text detection

2. You are planning a Microsoft Foundry project named Project1 that will contain multiple agents.
Each agent will access the same Azure AI Search resource.
You need to recommend a solution to centrally manage the Azure AI Search credentials within Project1. The solution must be implemented across all the agents.
What should you recommend?

A) Create a managed private endpoint that connects to the Azure AI Search resource.
B) Disable key-based access control on the Azure AI Search resource.
C) Enable role-based access control (RBAC) for the Azure AI Search resource.
D) Add a connection to the Azure AI Search resource.

3. You have a Semantic Kernel agent that provides answers to product questions.
You plan to extend the capabilities of the agent to answer questions about the status of orders.
You need to ensure that the agent answers order status questions as quickly as possible. The solution must minimize development effort.
What should you include in the solution?

A) a plugin
B) an agent
C) a function
D) a kernel

4. You have a Microsoft Foundry project that generates product marketing images from text prompts.
After publishing several images, the legal team at your company identifies a competitor's logo on a sign in the background of an image.
You need to remove only the logo, while preserving the rest of the image.
What should you do?

A) Modify the original prompt to exclude brand names.
B) Increase the prompt guidance strength.
C) Apply a mask-based inpainting edit to the part of the image that contains the logo.
D) Rerun the prompt by using a different random seed.

5. You are creating an agent workflow in a Microsoft Foundry project to support natural voice interactions.
The agent must receive continuous audio input, convert the input into text for reasoning, and then return spoken responses to a user. The workflow must meet the following requirements:
- Support turn-taking dynamics, where the agent begins to generate the
speech output before the user finishes speaking.
- Operate with low latency to maintain conversational experience.
You need to enable both speech to text and text to speech in a real-time agent interaction.
What should you do?

A) Use batch transcription to convert the audio input and return text responses from the agent.
B) Use speech translation to convert the audio into another language and return the translated text.
C) Use an embeddings model to encode the audio, and then decode the audio into text and speech.
D) Use real-time speech to text for incoming audio and text to speech for agent responses.

Solutions: