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Introduction to AI-102: Designing and Implementing an Azure AI Solution Exam
Candidates for AI-102 Exam are seeking to prove fundamental knowledge and skills in Designing and Implementing an Azure AI Solution domain. Before taking this exam, aspirants ought to have a solid fundamental information of the concepts shared in preparation guide as well as basic understanding of Azure administration, Azure development, and DevOpss would give an added edge.
This exam validates the ability to use the various services within the Microsoft Azure Artificial Intelligence (AI) portfolio.
It is suggested that professionals accustomed to the ideas and also the technologies represented here by taking relevant training courses. Candidates are expected to have some hands-on experience on bot services that use Language Understanding , bots with Azure Application Insights, creating a GPU, FPGA, or CPU-based solution, implementing AI workflow.
After passing this exam, candidates get a certificate from Microsoft that helps them to demonstrate their proficiency to their clients and employers.
Microsoft AI-102 Korean Exam Overview:
| Certification Vendor: | Microsoft |
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Exam Price: | $165 USD (varies by region: £113 GBP, €126 EUR) |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals (AI-900) Microsoft Certified: Azure Data Scientist Associate Microsoft Certified: Azure Developer Associate |
| Passing Score: | 700 (scaled score out of 1000) |
| Certificate Validity Period: | 1 year (renewable via free online assessment) |
| Real Exam Qty: | 40-60 |
| Available Languages: | English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Italian, Indonesian |
| Exam Format: | Multiple choice, Multiple select, Drag-and-drop, Case studies, Hot area, Performance-based scenarios |
| Exam Duration: | 100 minutes |
| Recommended Training: | Microsoft Learn Learning Paths for AI-102 AI-102T00: Designing and Implementing a Microsoft Azure AI Solution |
| Exam Registration: | Pearson VUE Scheduling Microsoft Certification Exam Registration |
| Sample Questions: | Microsoft AI-102 Korean Sample Questions |
| Exam Way: | Online proctored (OnVUE) or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended: experience with Azure services, AI concepts, and proficiency in Python or C#; AI-900 certification is recommended but not required |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ai-102 |
What is the duration, language, and format of AI-102: Designing and Implementing an Azure AI Solution Exam
- 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
- Type of Questions: This test format is multiple choice.
- Language: English, Japanese, Chinese (Simplified), Korean.
- Passing Score: 700 / 1000
- This is beta exam.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Microsoft AI-102 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Implement natural language processing solutions | 15-20% | - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots - Implement translation and summarization |
| Implement computer vision solutions | 10-15% | - Process and index video content - Integrate vision capabilities into applications - Extract text and handwriting from images - Analyze images and detect objects/features - Build and deploy custom vision models |
| 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 |
| Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Create and configure Azure AI resources - Plan solutions aligned with responsible AI principles - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Select suitable AI models |
| Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Understand agent use cases and types - Build agents with Microsoft Foundry Agent Service - Test, deploy, and optimize agents |
| Implement knowledge mining and information extraction solutions | 15-20% | - Implement intelligent search and retrieval - Ingest and process structured/unstructured data - Extract entities, relationships, and key phrases - Build knowledge bases and search indexes |
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