Updated: Sep 22, 2026
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Certificate Validity Period: | 1 year (renewable annually via Microsoft certification renewal assessment) |
| Exam Duration: | 100-120 |
| Exam Price: | USD 165 (varies by country/region) |
| Exam Format: | Multiple response, Multiple choice, Case studies, Drag and drop, Build/review solution scenarios |
| Real Exam Qty: | 40-60 (approximate range) |
| Passing Score: | 700 (out of 1000) |
| Available Languages: | Portuguese (Brazil), German, French, Japanese, Korean, Spanish (Latin America), English, Simplified Chinese |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals (AI-900) |
| Recommended Training: | Azure AI Engineer Associate Study Resources Microsoft Learn AI-102 Learning Path |
| Exam Registration: | Microsoft Learn AI-102 Certification Page Microsoft Certification Exam Registration (Pearson VUE) |
| Sample Questions: | Microsoft AI-102日本語 Sample Questions |
| Exam Way: | Online proctored or onsite test center (Pearson VUE) |
| Pre Condition: | No formal prerequisites required, but familiarity with Azure fundamentals and AI/ML concepts is recommended |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/ |
Candidates for Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution build, manage, and deploy AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework.
Their responsibilities include participating in all phases of AI solutions development—from requirements definition and design to development, deployment, maintenance, performance tuning, and monitoring.
They work with solution architects to translate their vision and with data scientists, data engineers, IoT specialists, and AI developers to build complete end-to-end AI solutions.
Candidates for this exam should be proficient in C# or Python and should be able to use REST-based APIs and SDKs to build computer vision, natural language processing, knowledge mining, and conversational AI solutions on Azure.
They should also understand the components that make up the Azure AI portfolio and the available data storage options. Plus, candidates need to understand and be able to apply responsible AI principles.
Part of the requirements for: Microsoft Certified: Azure AI Engineer Associate
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
| Section | Objectives |
|---|---|
| Topic 1: Plan and Manage an Azure AI Solution | - Plan solution requirements and architecture - Manage security, compliance, and responsible AI - Select appropriate Azure AI services |
| Topic 2: Implement Knowledge Mining and Document Intelligence | - Build Azure AI Search solutions - Enrich and index data for search scenarios - Implement document intelligence solutions |
| Topic 3: Implement Computer Vision Solutions | - Implement custom vision models - Analyze images and videos using Azure AI Vision - Extract information using OCR and form recognition |
| Topic 4: Implement Generative AI Solutions | - Integrate prompt engineering techniques - Build retrieval-augmented generation (RAG) solutions - Implement Azure OpenAI Service solutions |
| Topic 5: Implement Natural Language Processing Solutions | - Translate and interpret language using Azure AI services - Implement question answering and conversational AI - Analyze text using Azure AI Language |
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