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How much AI-102: Designing and Implementing an Azure AI Solution Exam Cost
The price of the Microsoft Mobility and Devices Fundamentals exam is $165 USD, for more information related to exam price please visit to Microsoft Training website as prices of Microsoft exams fees get varied country wise.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
Prep Options to Choose
The preparation process for the exam is a vital step on your way of passing the test, that’s why you need to find the most actual and reliable resources. Microsoft offers two options for you to choose from online free training or instructor-led, which is a paid one. For example, the free training represents a collection of learning paths each of which contains the different number of modules, from one to five. Thus, you can choose which ones to follow: Prepare for AI engineering (1 module), Process and Translate Speech with Azure Cognitive Speech Services (2 modules), Create computer vision solutions with Azure Cognitive Services (3 modules), to name a few. The paid course is known to be Course AI-102T00: Designing and Implementing a Microsoft Azure AI Solution and lasts for 4 days. It is intended for software developers interested in developing skills to build AI infused apps that use Azure Cognitive Search and Services, and Microsoft Bot Framework.
In addition, you can check the Amazon website to find the books on the topics included in the exam to ace it from the first attempt. Only after the successful passing the AI-102 exam you will earn the Microsoft Certified: Azure AI Engineer Associate certification. So, good luck!
Microsoft AI-102 Exam Overview:
| Certification Vendor: | Microsoft |
| Exam Name: | Designing and Implementing a Microsoft Azure AI Solution |
| Exam Number: | AI-102 |
| Related Certifications: | Microsoft Certified: Azure AI Fundamentals (AI-900) Microsoft Certified: Azure Data Scientist Associate Microsoft Certified: Azure Developer Associate |
| Available Languages: | English, Japanese, Chinese (Simplified), Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Italian, Indonesian |
| Certificate Validity Period: | 1 year (renewable via free online assessment) |
| Exam Duration: | 100 minutes |
| Exam Price: | $165 USD (varies by region: £113 GBP, €126 EUR) |
| Exam Format: | Multiple choice, Multiple select, Drag-and-drop, Case studies, Hot area, Performance-based scenarios |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700 (scaled score out of 1000) |
| Recommended Training: | AI-102T00: Designing and Implementing a Microsoft Azure AI Solution Microsoft Learn Learning Paths for AI-102 |
| Exam Registration: | Microsoft Certification Exam Registration Pearson VUE Scheduling |
| Sample Questions: | Microsoft AI-102 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 |
Microsoft AI-102 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Create and configure Azure AI resources - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining - Monitor, optimize, and secure AI solutions - Select appropriate Microsoft Foundry Services - Plan solutions aligned with responsible AI principles |
| Topic 2: Implement generative AI solutions | 15-20% | - Orchestrate multiple models and containers - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Deploy and manage generative models |
| Topic 3: Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Extract entities, relationships, and key phrases - Implement intelligent search and retrieval - Ingest and process structured/unstructured data |
| Topic 4: Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection |
| Topic 5: Implement an agentic solution | 5-10% | - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Test, deploy, and optimize agents |
| Topic 6: Implement computer vision solutions | 10-15% | - Analyze images and detect objects/features - Build and deploy custom vision models - Process and index video content - Integrate vision capabilities into applications - Extract text and handwriting from images |
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