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Microsoft AI-102 exam is designed for individuals who have a strong understanding of artificial intelligence (AI) and how it can be implemented in Microsoft Azure. AI-102-KR exam focuses on the design and implementation of AI solutions that can help businesses improve their operations, increase efficiency, and generate insights from data.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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| Section | Weight | Objectives |
|---|---|---|
| Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback |
| Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Develop multi-agent workflows and orchestration |
| Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles - Create and configure Azure AI resources - Select suitable AI models - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions |
| Implement computer vision solutions | 10-15% | - Process and index video content - Extract text and handwriting from images - Analyze images and detect objects/features - Integrate vision capabilities into applications - Build and deploy custom vision models |
| Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases |
| Implement natural language processing solutions | 15-20% | - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots - Implement translation and summarization - Customize and deploy NLP models |
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