Exam Name: Designing and Implementing a Microsoft Azure AI Solution
Certification Provider: Microsoft
Corresponding Certification: Azure AI Engineer Associate
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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.
What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam
- This is beta exam.
- Type of Questions: This test format is multiple choice.
- Language: English, Japanese, Chinese (Simplified), Korean.
- Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
- Length of Examination: 50 mins
- Passing Score: 700 / 1000
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Skills measured
- Implement natural language processing solutions (20-25%)
- Plan and manage an Azure Cognitive Services solution (15-20%)
- Implement Computer Vision solutions (20-25%)
- Implement knowledge mining solutions (15-20%)
- Implement conversational AI solutions (15-20%)
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Schedule exam
Languages: English, Japanese, Chinese (Simplified), Korean
Retirement date: none
This exam measures your ability to accomplish the following technical tasks: plan and manage an Azure Cognitive Services solutions; implement Computer Vision solutions; implement natural language processing solutions; implement knowledge mining solutions; and implement conversational AI solutions.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement computer vision solutions | 10-15% | - Analyze images and detect objects/features - Process and index video content - Build and deploy custom vision models - Extract text and handwriting from images - Integrate vision capabilities into applications |
| Topic 2: Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Create and configure Azure AI resources - Plan solutions aligned with responsible AI principles - Select appropriate Microsoft Foundry Services - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions |
| Topic 3: 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 4: 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 |
| Topic 5: Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots |
| Topic 6: Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data |
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