Microsoft Updated AI-102 Exam Questions and Answers by eddison

The requirement:

You have a system monitoring temperature data from a single data stream.

The system must generate an alert in response to atypical values.

The solution must minimize development effort.

Analysis of Options:

Univariate Anomaly Detection

Designed for detecting anomalies in a single time series (e.g., temperature, pressure, humidity, sales).

Since the system monitors temperature only, this is a classic univariate case.

Provides simple integration with minimal effort.

Correct choice.

Azure Stream Analytics

Can process real-time streaming data and detect conditions (with custom queries).

However, it requires more development effort since you would need to manually code logic for anomaly detection.

Not the minimal-effort option.

Metric alerts in Azure Monitor

Used to trigger alerts on predefined thresholds (static rules).

Not intelligent anomaly detection—does not automatically learn patterns from data.

Would require manual threshold setup, which is not efficient for anomaly detection.

Multivariate Anomaly Detection

Used when analyzing multiple related time series (e.g., temperature, pressure, vibration all together).

Since this scenario only has one variable (temperature), multivariate is unnecessary and adds complexity.

Correct Answer: A. Univariate Anomaly Detection

Microsoft References

Azure AI Anomaly Detector – Univariate

Multivariate Anomaly Detector

Difference between univariate and multivariate anomaly detection

In Azure Stream Analytics, queries are defined using a SQL-like query language specifically designed for real-time analytics over streaming data.

The language is often referred to as Stream Analytics Query Language (SAQL).

It is very similar to T-SQL (Transact-SQL) but extended with additional features for temporal (time-based) operations, stream joins, aggregations over windows, and event handling.

With this language, you can perform operations like filtering, projections, aggregations, joins, and even machine learning model scoring on data streams.

Reviewing the options:

SQL – Correct. Azure Stream Analytics jobs are defined using a SQL-like language.

XML – Incorrect. XML is used for data representation, not defining queries in Stream Analytics.

YAML – Incorrect. YAML is commonly used for configuration files, not streaming queries.

KOL – Incorrect. This is not a relevant query language.

Correct Answer: A. SQL

Microsoft References

Introduction to Azure Stream Analytics query language

Query overview for Stream Analytics

You are developing a speech translation service for recording lectures given in English (United Kingdom). The goal is to provide transcripts in multiple target languages: English, French, Spanish, and German.

Key requirements from the code snippet:

Source Language (Recognition Language):

config.SpeechRecognitionLanguage = " en-GB " ;

The input is English (UK).

Target Languages:

You need to define a list of supported target languages. Since English, French, Spanish, and German are supported, the correct syntax is:

var lang = new List < string > () { " en " , " fr " , " de " , " es " };

This uses ISO language codes expected by the Translator API ( " fr " = French, " de " = German, " es " = Spanish).

Recognizer Type:

Since this is speech translation, you must use:

using var recognizer = new TranslationRecognizer(config, audioConfig);

The TranslationRecognizer class is specifically for translating speech input into multiple languages.

Completed Code

static async Task TranslateSpeechAsync ()

{

var config = SpeechTranslationConfig.FromSubscription( " 69cad5cc-0ab3-4704-bdff-abf4aa07d85 " , " uksouth " );

var lang = new List < string > () { " en " , " fr " , " de " , " es " };

config.SpeechRecognitionLanguage = " en-GB " ;

lang.ForEach(config.AddTargetLanguage);

using var audioConfig = AudioConfig.FromDefaultMicrophoneInput();

using var recognizer = new TranslationRecognizer(config, audioConfig);

var result = await recognizer.RecognizeOnceAsync();

if (result.Reason == ResultReason.TranslatedSpeech)

{

foreach ( var element in result.Translations)

{

AppendToTranscriptFile(element.Value, element.Key);

}

}

}

Final Answer (Answer Area Selections)

First Blank: { " en " , " fr " , " de " , " es " }

Second Blank: TranslationRecognizer

Microsoft References

Speech Translation with Speech SDK

TranslationRecognizer class

Speech service supported languages