Microsoft Updated AI-102 Exam Questions and Answers by orin

Comprehensive Detailed ExplanationThe scenario:

You are building an Azure WebJob to create knowledge bases from an array of URLs.

You already have a QnAMakerClient object instantiated with the relevant API keys.

You need to know what steps are required to create a knowledge base programmatically.

CreateKbDTO is the request payload for creating a knowledge base.

It contains the name of the knowledge base and its sources, which may include:

A list of URLs.

A list of QnA pairs (QnADTO).

A list of files (FileDTO).

In this case, since the WebJob provides URLs, they will be passed inside the CreateKbDTO.Sources property.

Once the CreateKbDTO object is defined, you use the QnAMakerClient to send the request:

var response = await client.Knowledgebase.CreateAsync(createKbDTO);

This triggers the asynchronous creation of a new knowledge base in the QnA Maker service.

A. Create a list of FileDTO objects: Not required here, because the question specifies URLs, not files.

C. Create a list of QnADTO objects: Also not needed, since you’re not directly supplying QnA pairs; the knowledge base will be built from URLs.

Step 1 – Create a CreateKbDTO objectStep 2 – Call client.Knowledgebase.CreateAsyncWhy not A or C?

Correct AnswerB. Call the client.Knowledgebase.CreateAsync method.

D. Create a CreateKbDTO object.

QnA Maker – Create Knowledge Base API

QnAMakerClient Class – Azure SDK for .NET

CreateKbDTO Class

Microsoft References

For a social media messaging app that must identify the language of text messages in real time, the most direct SDK is the Azure AI Translator – Text Translation SDK. Its client libraries (e.g., Azure.AI.Translation.Text in .NET) include a language detection operation that returns the detected language code and a confidence score, which is exactly what you need for real-time text scenarios.

Other options are not a fit:

Microsoft.CognitiveServices.Speech is the Speech SDK for speech-to-text, TTS, and speech translation (audio), not text-only language detection.

Azure.AI.Translation.Document targets asynchronous document translation workflows, not short text message detection. Microsoft Learn

Azure.AI.Translation.Speech isn’t the package used; speech translation is covered by the Speech SDK package above. Microsoft Learn

Microsoft References

Text Translation SDK overview (supports language detection): Azure AI Translator. Microsoft Learn

DetectedLanguage in Azure.AI.Translation.Text (returned by detect operation). Microsoft Learn

Quickstart: Translator text client libraries. Microsoft Learn

Install/use the Speech SDK (contrast with text scenario). Microsoft Learn

Document Translation SDK overview (not applicable to short text detection). Microsoft Learn

With Azure OpenAI, you don’t call a raw “model name” directly; you call a deployment of that model. SDKs and REST require:

the resource endpoint,

the API key (or Entra ID token), and

the deployment name to target the specific model instance.

References

Azure OpenAI quickstart (connect using endpoint, key, and deployment name).https://learn.microsoft.com/azure/ai-services/openai/quickstart

Chat/completions—path uses /deployments/{deployment-id}.https://learn.microsoft.com/azure/ai-services/openai/reference#chat-completions

You have press releases stored as PDF files. The task involves two parts:

Extract text

The correct service for OCR and text extraction from images and PDFs is Azure Computer Vision (specifically, the OCR and Read API).

While Form Recognizer can also extract text, it is primarily used for structured documents like invoices, receipts, or forms. Since the documents here are press releases (unstructured text), the best service is Computer Vision.

Perform sentiment analysis

Sentiment analysis falls under natural language processing (NLP).

The correct service is Azure AI Language (Text Analytics API).

It provides sentiment analysis, opinion mining, key phrase extraction, entity recognition, and more.

Why not other options?

Azure Cognitive Search is used for search indexing, not OCR or sentiment.

Form Recognizer specializes in structured document extraction, not sentiment analysis.

Computer Vision cannot perform sentiment analysis (only visual/text extraction).

Correct Answer:

Extract text → Computer Vision

Perform sentiment analysis → Language

Computer Vision Read OCR

Language service – Sentiment Analysis

Microsoft References