Passing exam with AI-102日本語 latest training materials

Correct Answer:

Explanation:

To create a single multi-service Cognitive Services resource (now Azure AI Services) that provides one key
/endpoint for multiple services , consolidates billing, and allows adding services like Text Analytics (sentiment analysis) and Computer Vision (OCR) from the same resource, you must:
Use the Azure Resource Manager (ARM) REST API with PUT to create or update the account:
PUT /subscriptions/{subId}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{name}?
api-version=2017-04-18
Set " kind " : " CognitiveServices " to create the multi-service account (not a single-service kind like ComputerVision or TextAnalytics).
This satisfies the requirements: single key/endpoint, consolidated billing, and future Computer Vision use.
Microsoft Azure AI Solution References
ARM REST for Cognitive Services accounts (create/update via PUT , multi-service " kind " : " CognitiveServices " ).
https://learn.microsoft.com/azure/ai-services/management/resource-manager-create-account Azure AI Services multi-service resource (single endpoint/key across services).
https://learn.microsoft.com/azure/ai-services/multi-service-resource

Correct Answer:

Explanation:

Correct Answer:

Explanation:

Comprehensive Detailed Explanation
When an indexer runs in Azure AI Search, it processes each document through a fixed series of stages:
Document cracking
The indexer opens the item (file/row) and extracts text, images, and metadata, creating the root of the enriched document (/document). This is always the first stage.
Field mappings
Next, source fields are mapped directly to target index fields before any transformations . Field mappings occur after document cracking but before skillset execution . Microsoft Learn Skillset execution Built-in or custom skills (for example, language and sentiment analysis in your scenario) run and write outputs into the in-memory enriched document. Microsoft Learn Output field mappings Because skill outputs live only in memory, you must define output field mappings to route selected nodes of the enriched document into index fields. This step comes after skillset execution.
Push to index
Finally, the indexer hands off raw and enriched content to the search index (the physical data structures) so it becomes searchable-i.e., the content is "pushed to the index." Microsoft Learn This order- document cracking # field mappings # skillset execution # output field mappings # push to index -ensures raw content is extracted, direct source-to-index mappings are applied, AI enrichment is performed, enriched outputs are projected to fields, and the completed documents are written into the index.
Microsoft Azure AI References
Indexers in Azure AI Search - Stages of indexing (Document cracking; Field mappings; Skillset execution; Output field mappings, with field mappings occurring before transformations). Microsoft Learn Skillset concepts (Output of skillset is routed to the index via output field mappings after skillset execution).
Microsoft Learn
AI enrichment concepts (Field mappings move raw source content to the index; output field mappings move enriched content; indexing ingests raw and enriched content into the physical index). Microsoft Learn Annotations & enriched document tree (Enriched document is created during document cracking at
/document). Microsoft Learn

Correct Answer:

Explanation:

The question describes:
An Azure subscription with an Azure AI Content Safety resource.
A social media application where users can upload images.
The requirement is to moderate inappropriate content in those uploaded images.
In Azure AI Content Safety SDKs:
You create a ContentSafetyClient by providing the endpoint and key.
The ContentSafetyClient exposes methods such as:
AnalyzeText() # For text moderation
AnalyzeImage() # For image moderation
Let's review the code structure:
public static void Analyze ( AnalyzeImageOptions request )
{
var endpoint = Environment.GetEnvironmentVariable( " ENDPOINT " );
var key = Environment.GetEnvironmentVariable( " KEY " );
var client = new ContentSafetyClient( new Uri(endpoint), new AzureKeyCredential(key)); return client.AnalyzeImage(request);
}
First dropdown: must be ContentSafetyClient to instantiate the correct client for Azure AI Content Safety.
Second dropdown: since the requirement is image moderation, we must call client.AnalyzeImage(request) .
Other options:
BlocklistClient # used for custom blocklists, not full moderation.
TextCategoriesAnalysis # refers to text analysis categories, not suitable here.
AnalyzeText # would be used only for text moderation.
Therefore, the correct completion is:
ContentSafetyClient
client.AnalyzeImage(request)
The answer:
First dropdown: ContentSafetyClient
Second dropdown: client.AnalyzeImage(request)
Microsoft References
Azure AI Content Safety - Analyze images
Azure AI Content Safety SDK documentation
ContentSafetyClient class

Correct Answer:

Explanation:
Stream processing has access to the most recent data received or data within a rolling time window. # Yes Batch processing must occur immediately and have latency in the order of seconds or milliseconds. # No Stream processing is used for simple response functions, aggregates, or calculations such as rolling averages.
# Yes
Comprehensive Detailed Explanation
Stream processing has access to the most recent data received or data within a rolling time window.
Correct.
Stream processing handles real-time or near real-time data.
It operates on a continuous data stream and often uses a rolling time window for analytics.
The answer: Yes
Batch processing must occur immediately and have latency in the order of seconds or milliseconds.
Incorrect.
Batch processing is designed for large volumes of data collected over time.
It typically has high latency (minutes, hours, or even days), not immediate execution.
The answer: No
Stream processing is used for simple response functions, aggregates, or calculations such as rolling averages.
Correct.
Common stream analytics tasks include event-driven responses, real-time aggregations, anomaly detection, and rolling averages.
The answer: Yes
Correct Answers:
Yes
No
Yes
Microsoft References
Batch vs. Stream processing in Azure
Azure Stream Analytics overview