Microsoft AI-102 Korean Actual Free Exam Questions & Community Discussion

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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

Explanation:

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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

Explanation:
In user want to change to deploy offline model
1. Change model domain to compact model
2. Retrain compact model
3. Export model
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/export-your-model

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