PDF Version DemoWho 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.
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AI-102: Designing and Implementing an Azure AI Solution Exam Certified Professional salary
The average salary of a AI-102: Designing and Implementing an Azure AI Solution Exam Certified Expert in
- England - 90,532 POUND
- Europe - 90,547 EURO
- India - 20,00,327 INR
- United State - 120,000 USD
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Plan solutions aligned with responsible AI principles - Select suitable AI models - Create and configure Azure AI resources |
| Topic 2: Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes - Ingest and process structured/unstructured data |
| Topic 3: Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types |
| Topic 4: Implement natural language processing solutions | 15-20% | - Perform text analysis, sentiment detection, and language detection - Implement translation and summarization - Build conversational AI and chatbots - Customize and deploy NLP models |
| Topic 5: Implement generative AI solutions | 15-20% | - Apply prompt engineering and fine-tuning - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback - Deploy and manage generative models - Orchestrate multiple models and containers |
| Topic 6: Implement computer vision solutions | 10-15% | - Build and deploy custom vision models - Process and index video content - Analyze images and detect objects/features - Extract text and handwriting from images - Integrate vision capabilities into applications |
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