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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.
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Before enrolling in the process of taking the AI-102 exams, candidates should be skilled in implementing Python and C#, using APIs and SDKs based on REST to create natural language processing solutions, computer vision solutions, and knowledge mining and communicative AI solutions based on Azure. In addition, such specialists should be knowledgeable of the elements that create the Azure AI portfolio as well as the data storage options. To add more, they should be able to implement AI principles appropriately.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
| Section | Weight | Objectives |
|---|---|---|
| Implement Natural Language Processing Solutions | 20-25% | - Build question answering solutions - Create conversational AI solutions with Azure AI Bot Service - Translate text and speech - Implement speech capabilities using Azure AI Speech - Analyze text using Azure AI Language |
| Plan and Manage an Azure AI Solution | 15-20% | - Select appropriate Azure AI services and technologies - Plan and configure secure AI solutions - Manage AI costs and resource allocation - Implement governance and compliance for AI solutions |
| Implement Decision Support Solutions | 10-15% | - Monitor and optimize decision support solutions - Integrate Azure AI services into applications - Design and implement decision automation |
| Implement Computer Vision Solutions | 15-20% | - Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service - Process video and generate insights - Analyze images using Azure AI Vision - Implement object detection and image classification |
| Implement Generative AI Solutions | 10-15% | - Apply responsible AI practices - Implement prompt engineering techniques - Integrate Azure OpenAI models into applications - Use Azure OpenAI Service for generative AI |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Create custom skills for Azure AI Search - Implement semantic and vector search - Design document processing pipelines - Implement Azure AI Search solutions |
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