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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement Generative AI Solutions10-15%- Implement prompt engineering techniques
- Use Azure OpenAI Service for generative AI
- Apply responsible AI practices
- Integrate Azure OpenAI models into applications
Topic 2: Implement Natural Language Processing Solutions20-25%- Analyze text using Azure AI Language
- Implement speech capabilities using Azure AI Speech
- Build question answering solutions
- Translate text and speech
- Create conversational AI solutions with Azure AI Bot Service
Topic 3: Implement Knowledge Mining and Document Intelligence Solutions15-20%- Implement Azure AI Search solutions
- Design document processing pipelines
- Create custom skills for Azure AI Search
- Implement semantic and vector search
Topic 4: Plan and Manage an Azure AI Solution15-20%- Implement governance and compliance for AI solutions
- Select appropriate Azure AI services and technologies
- Manage AI costs and resource allocation
- Plan and configure secure AI solutions
Topic 5: Implement Decision Support Solutions10-15%- Monitor and optimize decision support solutions
- Integrate Azure AI services into applications
- Design and implement decision automation
Topic 6: Implement Computer Vision Solutions15-20%- Analyze images using Azure AI Vision
- Implement Azure AI Face service
- Process video and generate insights
- Implement object detection and image classification
- Read and process documents using Azure AI Document Intelligence

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q200-Q205):

NEW QUESTION # 200
You are building a natural language model.
You need to enable active learning.
What should you do?

Answer: C

Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-queries-to-enable-active-learning


NEW QUESTION # 201
Which scenario is an example of a streaming workload?

Answer: A

Explanation:
* A streaming workload means data is generated continuously and ingested in near real time.
* Telemetry from edge/IoT devices is a classic example of streaming workloads because the devices constantly push data (sensor readings, logs, metrics).
* A. sending transactions daily # batch workload (not streaming).
* B. sending metadata every 30 minutes # periodic batch, not continuous streaming.
* C. sending old transactions to archive # cold data archival, not streaming.
Reference: Azure Stream Analytics overview


NEW QUESTION # 202
You are building a call handling system that will receive calls from French-speaking and German-speaking callers. The system must perform the following tasks;
* Capture inbound voice messages as text.
* Replay messages in English on demand.
Which Azure Cognitive Services should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 203
You have an Azure subscription that contains an Azure Al Content Safety resource named CS1.
You create a test image that contains a circle.
You submit the test image to CS1 by using the curl command and the following command-line parameters.

What should you expect as the output?

Answer: A,B


NEW QUESTION # 204
You are developing a photo application that will find photos of a person based on a sample image by using the Face API.
You need to create a POST request to find the photos.
How should you complete the request? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/detectwithurl
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar


NEW QUESTION # 205
......

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