Last Updated: Aug 20, 2026
No. of Questions: 425 Questions & Answers with Testing Engine
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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!
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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| Section | Weight | Objectives |
|---|---|---|
| Implement knowledge mining and information extraction solutions | 15-20% | - Ingest and process structured/unstructured data - Extract entities, relationships, and key phrases - Implement intelligent search and retrieval - Build knowledge bases and search indexes |
| Plan and manage an Azure AI solution | 20-25% | - Select appropriate Microsoft Foundry Services - Select suitable AI models - 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 |
| Implement computer vision solutions | 10-15% | - Extract text and handwriting from images - Analyze images and detect objects/features - Process and index video content - Build and deploy custom vision models - Integrate vision capabilities into applications |
| Implement natural language processing solutions | 15-20% | - Build conversational AI and chatbots - Perform text analysis, sentiment detection, and language detection - Customize and deploy NLP models - Implement translation and summarization |
| Implement an agentic solution | 5-10% | - Build agents with Microsoft Foundry Agent Service - Understand agent use cases and types - Test, deploy, and optimize agents - Develop multi-agent workflows and orchestration |
| Implement generative AI solutions | 15-20% | - Orchestrate multiple models and containers - Apply prompt engineering and fine-tuning - Implement model monitoring and feedback - Integrate Azure OpenAI and other generative models - Deploy and manage generative models |
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