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Microsoft AI-102 is a certification exam that is designed to test the skills and knowledge of candidates in designing and implementing solutions that use Microsoft Azure AI. Designing and Implementing a Microsoft Azure AI Solution certification exam is intended for professionals who have a strong understanding of Microsoft Azure and its services, as well as experience in the design and deployment of AI solutions. AI-102 exam is designed to assess a candidate's ability to use Azure AI services to solve business problems and create intelligent applications.
The AI-102 Certification Exam covers a range of topics related to AI solution design and implementation. These include designing AI solutions, implementing AI workflows, deploying and managing AI models, and monitoring and optimizing AI solutions. AI-102 exam is intended for professionals who have expertise in machine learning, Azure AI services, and data science.
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Exam AI-102 contains five topics each of which is intended to check specific skills.
1. Plan and Manage an Azure Cognitive Services Solution
This topic implies your ability to choose the suitable Cognitive Services resource, create it, plan and design security for a Cognitive Services solution, and apply Cognitive Services containers. This means that you should be competent in selecting the appropriate cognitive service for solutions that refer to language analysis, speech, decision support, and vision. You also should possess skills to operate costs of Cognitive Services, create a Cognitive Services resource, and monitor a cognitive service. This part also checks how well you can operate Cognitive Services account keys, and protect Cognitive Services. Your knowledge of using Face API, Computer Vision, Speech, Text Analysis, and ability to integrate Cognitive Services Containers in Microsoft Azure will also be assessed.
2. Implement Computer Vision Solutions
The second topic is designed to check your skills in using the Computer Vision API to get image descriptions, define landmarks, find brands, edit content in images, and create thumbnails. In this part, you are expected to be able to detect faces and recognize them in images, analyze facial features, and match similar faces with the help of the Face API. Being competent in utilizing the Custom Vision service, you should demonstrate your skills in applying image classification and implementing an object detection solution. Besides, your ability to analyze video by implementing Azure Video Analyzer for Media will be measured.
3. Implement Natural Language Processing Solutions
In the third topic, candidates are required to show their skills in analyzing text by utilizing the Text Analytics service, control speech by implementing the Speech service, translate the text with the help of the Translator service. This domain also checks your proficiency in creating and optimizing an initial language model by utilizing LUIS, and finally, managing it.
4. Implement Knowledge Mining Solutions
In this domain, you will be required to have expertise related to applying a Cognitive Search solution, which implies creating data sources, identifying an index, running an indexer, and using synonyms. This topic also aims to evaluate your ability to apply an enrichment pipeline, use a knowledge store, operate a Cognitive Search solution and indexing.
5. Implement Conversational AI Solutions
This domain will evaluate your capacity in utilizing QnA Maker to make a knowledge base, creating and implementing conversation flow, creating a bot by utilizing either the Bot Framework Composer or the Bot Framework SDK. Finally, you will need to demonstrate your skills in integrating Cognitive Services into a bot.
NEW QUESTION # 358
You are developing an application that will use the Computer Vision client library. The application has the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 359
You have a monitoring solution that uses the Azure Al Anomaly Detector service.
You provision a server named Server! that has intermittent internet access.
You need to deploy the Azure Al Anomaly Detector to Server 1.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
The requirement:
* You are using Azure AI Anomaly Detector.
* You need to deploy it on Server1, which has intermittent internet access.
* This means you need to run the service locally using containers (Docker).
Step 1 - Install Docker Engine
* Before pulling or running any containers, Docker must be installed on Server1.
* Without Docker Engine, no container can be deployed.
Step 2 - Pull the container image
* Use docker pull to download the Anomaly Detector container image from Microsoft Container Registry.
* This requires internet access, so it should be done when connectivity is available.
Step 3 - Run the container
* After pulling the image, use docker run to start the Anomaly Detector container.
* This exposes a local REST API endpoint on Server1.
Step 4 - Query the local endpoint
* Once the container is running, you can query the prediction endpoint on Server1.
* This allows local inference without requiring continuous internet access.
Correct Sequence:
* Install the Docker Engine on Server1.
* From Server1, run the docker pull command.
* From Server1, run the docker run command.
* Query the prediction endpoint on Server1.
* Use Azure AI Anomaly Detector on containers
* Deploy Azure AI services in Docker containers
* Anomaly Detector container setup
NEW QUESTION # 360
You are building a chatbot.
You need to use the Content Moderator service to identify messages that contain sexually explicit language.
Which section in the response from the service will contain the category score, and which category will be assigned to the message? To answer, select the appropriate options in the answer area, NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 361
You are creating an enrichment pipeline that will use Azure Cognitive Search. The knowledge store contains unstructured JSON data and scanned PDF documents that contain text.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview
NEW QUESTION # 362
You are developing the knowledgebase by using Azure Cognitive Search.
You need to build a skill that will be used by indexers.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition
NEW QUESTION # 363
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