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Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam
The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.
AI-102: Designing and Implementing an Azure AI Solution Certification Path
The Microsoft Designing and Implementing an Azure AI Solution Certification includes only one AI-100 Exam.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Skills measured
- Implement Computer Vision solutions (20-25%)
- Implement natural language processing solutions (20-25%)
- Implement knowledge mining solutions (15-20%)
- Plan and manage an Azure Cognitive Services solution (15-20%)
- Implement conversational AI solutions (15-20%)
Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection - Implement translation and summarization |
| Topic 2: Implement generative AI solutions | 15-20% | - Implement model monitoring and feedback - Deploy and manage generative models - Apply prompt engineering and fine-tuning - Integrate Azure OpenAI and other generative models - Orchestrate multiple models and containers |
| Topic 3: Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service - Test, deploy, and optimize agents - Understand agent use cases and types |
| Topic 4: Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Extract entities, relationships, and key phrases - Implement intelligent search and retrieval - Build knowledge bases and search indexes |
| Topic 5: Plan and manage an Azure AI solution | 20-25% | - Monitor, optimize, and secure AI solutions - Select suitable AI models - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining |
| Topic 6: Implement computer vision solutions | 10-15% | - Analyze images and detect objects/features - Build and deploy custom vision models - Extract text and handwriting from images - Integrate vision capabilities into applications - Process and index video content |
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