AI-102 Practice Questions

Analysis:

Azure AI Bot Service (A): Helps build chatbots but does not store grounding data → ❌

Azure SQL (B): Possible storage, but not recommended for vector search grounding → ❌

Azure AI Document Intelligence (C): Extracts structured info, not used directly for grounding → ❌

Azure Blob Storage (D): Required for storing raw files used in retrieval-augmented generation (RAG) → ✅

Azure AI Search (E): Used to index, vectorize, and query data for grounding → ✅

Correct Answer:

D.  

The statement is:

" In an infrastructure as a service (IaaS) instance of Microsoft SQL Server on Azure, you manage the ______ that hosts SQL Server. "

Options:

Elastic pool → A PaaS concept in Azure SQL Database (used to share resources across multiple databases). Not IaaS.

MySQL server → Refers to Azure Database for MySQL (PaaS). Not related to SQL Server on IaaS.

PostgreSQL server → Refers to Azure Database for PostgreSQL (PaaS). Not related to SQL Server on IaaS.

Virtual machine → In IaaS, SQL Server is installed on an Azure VM. You manage the VM (OS, patches, SQL installation, backups, etc.). ✅

Thus, for IaaS, you are responsible for managing the virtual machine that hosts SQL Server.

Correct Answer: virtual machine

Microsoft References

SQL Server on Azure Virtual Machines overview

Compare Azure SQL Database (PaaS) vs SQL Server on VMs (IaaS)

Scenario Recap

You are building a streaming Speech-to-Text solution using the Speech SDK.

Input audio format: MP3 encoding

You must configure the audio stream format and the recognizer properly.

Code Analysis

Audio Format

For MP3 streams, the correct method is:

AudioStreamFormat.GetCompressedFormat(AudioStreamContainerFormat.MP3)

This creates an audio format object for compressed MP3 input.

Recognizer

Since the task is speech-to-text transcription, you need the SpeechRecognizer class.

Other options like KeywordRecognizer, SpeakerRecognizer, or SpeechSynthesizer are not appropriate (they handle keyword spotting, speaker identification, or text-to-speech).

Completed Code Snippet

var audioFormat = AudioStreamFormat.GetCompressedFormat(AudioStreamContainerFormat.MP3);

var speechConfig = SpeechConfig.FromSubscription( " 18c51a87-3a69-47a8-aedc-a54745f708a1 " , " westus " );

var audioConfig = AudioConfig.FromStreamInput(pushStream, audioFormat);

using ( var recognizer = new SpeechRecognizer(speechConfig, audioConfig))

{

var result = await recognizer.RecognizeOnceAsync();

var text = result.Text;

}

Final Answer (Answer Area Selections)

AudioFormat: AudioStreamFormat.GetCompressedFormat

Recognizer: SpeechRecognizer

Microsoft References

Speech SDK – AudioStreamFormat

SpeechRecognizer class

Comprehensive Detailed Explanation

You’re adding multiple images for each person into a PersonGroup using the Face API SDK.

File.OpenRead(imagePath) returns a Stream, so the using declaration must declare Stream t = File.OpenRead(imagePath) .

To upload an image from a stream to a person in a person group, call

faceClient.PersonGroupPerson.AddFaceFromStreamAsync(personGroupId, personId, t);

Putting it together:

Parallel.For( 0 , PersonCount, async i = >

{

Guid personId = persons[i].PersonId;

string personImageDir = $ " /path/to/person/ {i} /images " ;

foreach ( string imagePath in Directory.GetFiles(personImageDir, " *.jpg " ))

{

using (Stream t = File.OpenRead(imagePath))

{

await faceClient.PersonGroupPerson.AddFaceFromStreamAsync(

personGroupId, personId, t);

}

}

});

This loops the images for each person, opens each as a stream, and adds the face to the specified person in the person group.

References

Microsoft Docs – Face API: Add a face to a person ( AddFaceFromStreamAsync , AddFaceFromUrlAsync ) in PersonGroupPerson operations.

https://learn.microsoft.com/azure/ai-services/face/ (see SDK/PersonGroupPerson methods)

NET File.OpenRead returns Stream .

https://learn.microsoft.com/dotnet/api/system.io.file.openread

To quickly prototype harmful-content detection (e.g., discriminatory language) with minimal development, you should provision an Azure AI Content Safety resource in the Azure portal and then try it in Content Safety Studio using “Moderate text content.” Content Safety Studio lets you test text moderation, tune thresholds, and export sample code without writing much code up front. Creating an Azure OpenAI resource or using “Protected material detection for text” isn’t required for abusive/hate moderation; “protected material” targets copyrighted/credential leakage scenarios, not general toxicity.

Microsoft References:

Quickstart: Analyze text content (use Moderate text content in the studio; prerequisite is to create a Content Safety resource). Microsoft Learn

Azure AI Content Safety overview