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Microsoft AI-102 Exam Syllabus Topics:

Section	Weight	Objectives
Implement computer vision solutions	10-15%	- Process and index video content - Extract text and handwriting from images - Analyze images and detect objects/features - Build and deploy custom vision models - Integrate vision capabilities into applications
Implement an agentic solution	5-10%	- Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents
Implement generative AI solutions	15-20%	- Implement model monitoring and feedback - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers - Apply prompt engineering and fine-tuning - Deploy and manage generative models
Implement knowledge mining and information extraction solutions	15-20%	- Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Ingest and process structured/unstructured data
Plan and manage an Azure AI solution	20-25%	- Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Select suitable AI models
Implement natural language processing solutions	15-20%	- Build conversational AI and chatbots - Customize and deploy NLP models - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection

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Exam AI-102 Topic, AI-102 Exam Format

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q203-Q208):

NEW QUESTION # 203
You have receipts that are accessible from a URL.
You need to extract data from the receipts by using Form Recognizer and the SDK. The solution must use a prebuilt model.
Which client and method should you use?

A. the FormRecognizerClienc client and the ScarcRecognizeConcencFromUri method
B. the FormTrainingClienc client and the ScarcRecognizeContentFromUri method
C. the FormRecognizerClienc client and the ScarcRecognizeReceipcsFromUri method
D. the FormTrainingClient client and the ScarcRecognizeReceipcsFromUri method

Answer: D

Explanation:
To analyze receipts from a URL, use the StartRecognizeReceiptsFromUri method Example code:
private static async Task AnalyzeReceipt(
FormRecognizerClient recognizerClient, string receiptUri)
{
RecognizedFormCollection receipts = await recognizerClient.StartRecognizeReceiptsFromUri(new Uri(receiptUrl)).WaitForCompletionAsync(); Reference:
https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/quickstarts/client-library

NEW QUESTION # 204
You have a collection of press releases stored as PDF files.
You need to extract text from the files and perform sentiment analysis.
Which service should you use for each task? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

NEW QUESTION # 205
Hotspot Question
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 206
You need to build an app that will capture video meetings and perform the following actions:
- Generate subtitles in real time.
- Recognize speakers in the videos.
What should you use?

A. Azure AI Speech speech to text speaker recognition
B. Azure AI Video Indexer
C. Azure AI Custom Vision
D. Azure AI Speech speech to text meeting transcription

Answer: B

Explanation:
Azure AI Video Indexer is the ideal choice for analyzing video content, including the tasks of generating subtitles in real-time and recognizing speakers. Video Indexer uses AI to extract metadata, such as speech-to-text transcription, speaker identification, and other video analysis features. It is specifically designed to handle video files and process them comprehensively for such use cases.

NEW QUESTION # 207
Hotspot Question
You are building a bot and that will use Language Understanding.
You have a LUDown file that contains the following content.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
SelectItem is the intent, and each item below it are example utterances that capture ways users can express this intent. Entities in .lu files are denoted using {<entityName>=<labeled value>} notation. Taking from our sample code once again, you can find the bottom left entity within the following utterance: choose the {DirectionalReference=bottom left}.
https://github.com/solliancenet/tech-immersion-data-ai/blob/master/ai-exp1/README.md

NEW QUESTION # 208
......

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