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How to book the AI-102: Designing and Implementing an Azure AI Solution Exam
These are following steps for registering the AI-102: Designing and Implementing an Azure AI Solution exam.
- Step 1: Visit to Microsoft Learning and search for AI-102: Developing Solutions for Microsoft Azure.
- Step 2: Sign up/Login to Pearson VUE account
- Step 3: Select local centre based on your country, date, time and confirm with a payment method.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
How to study the AI-102: Designing and Implementing an Azure AI Solution Exam
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Designing and Implementing a Microsoft Azure AI Solution Exam Certification Details:
| Passing Score | 700 / 1000 |
| Exam Price | $165 (USD) |
| Exam Name | Microsoft Certified - Azure AI Engineer Associate |
| Duration | 130 mins |
| Schedule Exam | Pearson VUE |
| Sample Questions | Designing and Implementing a Microsoft Azure AI Solution Sample Questions |
| Books / Training | Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Number of Questions | 40-60 |
| Exam Code | AI-102 |
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Plan solutions aligned with responsible AI principles - Monitor, optimize, and secure AI solutions - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Create and configure Azure AI resources - Select appropriate Microsoft Foundry Services |
| Topic 2: Implement generative AI solutions | 15-20% | - Integrate Azure OpenAI and other generative models - Implement model monitoring and feedback - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Deploy and manage generative models |
| Topic 3: Implement computer vision solutions | 10-15% | - Extract text and handwriting from images - Build and deploy custom vision models - Analyze images and detect objects/features - Process and index video content - Integrate vision capabilities into applications |
| Topic 4: Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Build knowledge bases and search indexes - Extract entities, relationships, and key phrases - Implement intelligent search and retrieval |
| Topic 5: Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Develop multi-agent workflows and orchestration - Test, deploy, and optimize agents - Understand agent use cases and types |
| Topic 6: Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Implement translation and summarization - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection |
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