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The Microsoft AI-102 exam focuses on various Azure services that are used to build AI solutions. The candidates are expected to have a good understanding of Azure Machine Learning, Cognitive Services, and Bot Framework. AI-102 exam also covers topics related to data storage, data processing, and data visualization using Azure services.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Microsoft AI-102 exam covers various topics related to designing and implementing AI solutions, such as data preparation, machine learning models, natural language processing, computer vision, and conversational AI. It also includes topics related to deploying and managing AI solutions on the Azure platform. AI-102 exam consists of both multiple-choice and lab-based questions, and candidates are required to demonstrate their practical skills in designing and implementing AI solutions on Azure. Passing AI-102 exam requires a deep understanding of Azure AI services and the ability to design and implement AI solutions to solve real-world business problems.
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Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement Natural Language Processing Solutions | 20-25% | - Create conversational AI solutions with Azure AI Bot Service - Build question answering solutions - Analyze text using Azure AI Language - Implement speech capabilities using Azure AI Speech - Translate text and speech |
| Implement Decision Support Solutions | 10-15% | - Integrate Azure AI services into applications - Design and implement decision automation - Monitor and optimize decision support solutions |
| Implement Generative AI Solutions | 10-15% | - Apply responsible AI practices - Use Azure OpenAI Service for generative AI - Implement prompt engineering techniques - Integrate Azure OpenAI models into applications |
| Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Create custom skills for Azure AI Search - Implement Azure AI Search solutions - Design document processing pipelines - Implement semantic and vector search |
| Implement Computer Vision Solutions | 15-20% | - Process video and generate insights - Implement Azure AI Face service - Implement object detection and image classification - Read and process documents using Azure AI Document Intelligence - Analyze images using Azure AI Vision |
| Plan and Manage an Azure AI Solution | 15-20% | - Manage AI costs and resource allocation - Implement governance and compliance for AI solutions - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies |
