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Microsoft AI-103 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Plan and Manage Azure AI Solutions | - Model selection and lifecycle management - Azure AI resource provisioning and configuration - Responsible AI principles and governance |
| Implement Computer Vision Solutions | - Image classification and object detection - OCR and document intelligence |
| Knowledge Mining and Information Retrieval | - Azure AI Search configuration - Indexing and semantic search - RAG (Retrieval Augmented Generation) patterns |
| Implement Natural Language Processing Solutions | - Text analytics and summarization - Language understanding and intent recognition - Translation and multilingual support |
| Develop Generative AI Applications and Agents | - AI agents architecture
|
Microsoft Developing AI Apps and Agents on Azure Preparation: Focused, Supported, Calm
- Implement Natural Language Processing Solutions ()
- Plan and Manage Azure AI Solutions ()
- Implement Computer Vision Solutions ()
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
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 an embeddings model to encode the audio, and then decode the audio into text and speech.
- B. Use real-time speech to text for incoming audio and text to speech for agent responses.
- C. Use batch transcription to convert the audio input and return text responses from the agent.
- D. Use speech translation to convert the audio into another language and return the translated text.
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
You are building a voice agent for a pharmacy. It must accept spoken questions, reply with synthesised speech, and accurately recognise specialised medicine names that a general speech model often mishears. Which capability should you configure?
- A. A custom speech model for speech-to-text within the agent
- B. Azure Translator to convert the audio
- C. Only the default text-to-speech voice
- D. Azure AI Document Intelligence on the audio stream
Correct Answer: A 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
You have an application that uses a prebuilt Azure Language model.
You need to generate a summary that meets the following requirements:
- Summarizes documents that contain multiple sentences
- Preserves the original sentence order
- Returns exactly three sentences
Which Language service feature should you use?
- A. extractive summarization
- B. key phrase extraction
- C. abstractive summarization
- D. sentiment analysis
Correct Answer: A 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
Users report that some responses omit required regulatory clauses, even when the clauses are present in the retrieved content.
You need to improve response completeness.
Solution: You increase the value of the max_tokensparameter.
Does this meet the goal?
- A. Yes
- B. No
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
You have a Microsoft Foundry project that contains a model deployment.
You have an application that calls the deployment by using the Azure OpenAI v1 API and DefaultAzureCredential.
The developers at your company receive HTTP 403 errors when they send inference requests, even after running az login.
You need to ensure that the developers can perform model inference. The solution must follow the principle of least privilege.
Which role-based access control (RBAC) role should you assign to the developers?
- A. Contributor
- B. Cognitive Services OpenAI User
- C. Cognitive Services Data Reader
- D. Cognitive Services User
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
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