Microsoft AI-103 Exam : Developing AI Apps and Agents on Azure

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Microsoft AI-103 Exam Syllabus Topics:

Microsoft Developing AI Apps and Agents on Azure Sample Questions:

Question 1

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 AI Video Indexer
B. Azure Vision in Foundry Tools Image Analysis
C. Azure AI Face
D. Azure Vision in Foundry Tools Spatial Analysis

Question 2

You have a Microsoft Foundry project that contains a Retrieval Augmented Generation (RAG) chat solution used by customer support agents.
You are adding an automated pre-production evaluation step to a CI/CD pipeline named Pipeline1. The evaluation will run against a labeled test dataset that contains support questions and the expected grounding context.
You need to ensure that Pipeline1 fails if unsupported content or a retrieval mismatch exceeds a defined threshold:
- responses include claims not supported by the retrieved source
content
- retrieved source content does not align with the labeled expected
context
Which two built-in evaluators should you use in Pipeline1? Each correct answer presents pat of the solution.
NOTE: Each correct selection is worth one point.

A. Coherence
B. Retrieval
C. Fluency
D. Groundedness
E. Response Completeness

Question 3

Hotspot Question
You are building a model to detect objects in images.
The performance of the model based on training data is shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Question 4

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 OpenAI text summarization
B. Azure OpenAI text classification
C. Azure AI Language custom text classification
D. Azure AI Language custom named entity recognition (NER)

Question 5

A finance team must extract named fields, such as invoice number and total, from invoices, and they need a per-field confidence score so that low-confidence values can be routed to a human reviewer. Which Azure Content Understanding mode should they use?

A. Neither, because confidence scoring requires Azure AI Document Intelligence
B. Pro mode
C. Either mode, because both return confidence scores
D. Standard mode

Solutions: