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Candidates for AI-102 Exam are seeking to prove fundamental knowledge and skills in Designing and Implementing an Azure AI Solution domain. Before taking this exam, aspirants ought to have a solid fundamental information of the concepts shared in preparation guide as well as basic understanding of Azure administration, Azure development, and DevOpss would give an added edge.
This exam validates the ability to use the various services within the Microsoft Azure Artificial Intelligence (AI) portfolio.
It is suggested that professionals accustomed to the ideas and also the technologies represented here by taking relevant training courses. Candidates are expected to have some hands-on experience on bot services that use Language Understanding , bots with Azure Application Insights, creating a GPU, FPGA, or CPU-based solution, implementing AI workflow.
After passing this exam, candidates get a certificate from Microsoft that helps them to demonstrate their proficiency to their clients and employers.
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Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.
Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and Manage an Azure AI Solution | 15-20% | - Manage AI costs and resource allocation - Plan and configure secure AI solutions - Select appropriate Azure AI services and technologies - Implement governance and compliance for AI solutions |
| Topic 2: Implement Computer Vision Solutions | 15-20% | - Implement object detection and image classification - Process video and generate insights - Read and process documents using Azure AI Document Intelligence - Implement Azure AI Face service - Analyze images using Azure AI Vision |
| Topic 3: Implement Decision Support Solutions | 10-15% | - Design and implement decision automation - Monitor and optimize decision support solutions - Integrate Azure AI services into applications |
| Topic 4: Implement Generative AI Solutions | 10-15% | - Use Azure OpenAI Service for generative AI - Apply responsible AI practices - Integrate Azure OpenAI models into applications - Implement prompt engineering techniques |
| Topic 5: Implement Knowledge Mining and Document Intelligence Solutions | 15-20% | - Design document processing pipelines - Implement semantic and vector search - Create custom skills for Azure AI Search - Implement Azure AI Search solutions |
| Topic 6: Implement Natural Language Processing Solutions | 20-25% | - Build question answering solutions - Analyze text using Azure AI Language - Create conversational AI solutions with Azure AI Bot Service - Translate text and speech - Implement speech capabilities using Azure AI Speech |
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