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What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam
- Passing Score: 700 / 1000
- Length of Examination: 50 mins
- Number of Questions: 40 to 60 questions(Since Microsoft does not publish this information, the number of exam questions may change without notice.)
- Language: English, Japanese, Chinese (Simplified), Korean.
- This is beta exam.
- Type of Questions: This test format is multiple choice.
The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification
- This certification will be judging your skills and knowledge on your understanding Designing and Implementing an Azure AI Solution concepts & Understanding of how to operate on Planning and Administering Designing and Implementing an Azure AI Solution .
- AI-102 credential delivers higher earning potential and increased promotion opportunities because it shows a good understanding of designing and implementing an Azure AI Solution
- AI-102 certification has more useful and relevant networks that help them in setting career goals for themselves. AI-102 networks provide them with the correct career guidance than non certified generally are unable to get.
- AI-102 certified candidates will be confident and stand different from others as their skills are more trained than non-certified professionals.
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For candidates that are aiming to develop their skills in building, operating, and deploying AI solutions with the help of such services as Azure Applied AI services and Azure Cognitive Services, the best variant is to pass the Microsoft AI-102 exam. This exam is all about designing and applying a Microsoft Azure AI Solution, and leads to getting the Microsoft Certified: Azure AI Engineer Associate certification.
Passing this exam implies that certified candidates are able to participate in all stages of AI solutions development from defining requirements to performance tuning and monitoring. These professionals cooperate with solution architects, as well as with data engineers and scientists, AI developers to show their vision and create comprehensive AI solutions.
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.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Implement translation and summarization - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models |
| Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Understand agent use cases and types - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service |
| Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Plan solutions aligned with responsible AI principles - Create and configure Azure AI resources - Select suitable AI models - Monitor, optimize, and secure AI solutions |
| Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases - Ingest and process structured/unstructured data - Build knowledge bases and search indexes |
| Implement computer vision solutions | 10-15% | - Integrate vision capabilities into applications - Extract text and handwriting from images - Build and deploy custom vision models - Process and index video content - Analyze images and detect objects/features |
| Implement generative AI solutions | 15-20% | - Deploy and manage generative models - Implement model monitoring and feedback - Apply prompt engineering and fine-tuning - Orchestrate multiple models and containers - Integrate Azure OpenAI and other generative models |
