Free Microsoft AI-103 Exam Dumps Questions & Answers

Hotspot Question
You have an Azure subscription.
You need to create a new resource that will generate fictional stores in response to user prompts.
The solution must ensure that the resource uses a customer-managed key to protect data.
How should you complete the script? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:
Box 1: OpenAI
To generate fictional stores in response to user prompts, you need a generative AI model (such as GPT-3.5 or GPT-4). The Azure OpenAI service natively supports this generative capability and allows you to secure your deployed models and data using customer-managed keys (CMK).
Box 2: --assign-identity
When defining the Azure Key Vault resource script to enable customer-managed keys (CMK), you must use --assign-identity (or assign-identity).
Reference:
https://learn.microsoft.com/en-us/azure/search/search-how-to-managed-identities

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 add a reflection pass that regenerates the response if the required clauses are missing.
Does this meet the goal?

• A.No
• B.Yes

You have a large collection of image files and PDF documents stored in an Azure Storage account. The documents contain tabular data.
You need to extract the tables into a structured format that can be imported into a database. The solution must minimize development effort. What should you use?

• A.Azure Document Intelligence in Foundry Tools
• B.Azure Vision in Foundry Tools
• C.Azure AI Video Indexer
• D.Azure Content Understanding in Foundry Tools

You have a Microsoft Foundry project that contains an agent.
The agent uses a knowledge source built from documents stored in Azure Blob Storage. The documents include digitally scanned PDFs that contain multipage tables.
You have an ingestion job that extracts only plain text, causing loss of table structure, headings, and page-number metadata.
Users frequently ask questions that require the retrieval of specific table rows across the pages.
You need to configure an ingestion job for a Retrieval Augmented Generation (RAG) pipeline that performs optical character recognition (OCR) on scanned PDFs, preserves tables and headings as structure-aware chunks, and stores page-number metadata with each chunk.
How should you configure the ingestion job?

• A.Use basic parsing and fixed-size chunking.
• B.Use OCR and page-level chunking.
• C.Use advanced data parsing to reingest the documents.
• D.Use page-level OCR extraction and store each page as a single chunk.

You are developing an app that will perform a sentiment analysis of social media posts by using the Azure AI Language service.
You perform a test on a sample post.
You need to quantify the results of the test.
Which JSON property should you review?

• A.confidenceThreshold
• B.confidenceScores
• C.relations
• D.sentiment