Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution
Proctored Microsoft certification exam focused on building and operating Azure AI solutions across multiple AI workloads.
- Type
- Written
- Duration
- 100 min
Exam sections
Plan and manage an Azure AI solution
This section covers selecting appropriate Azure AI services, managing resources, ensuring Responsible AI compliance, and monitoring costs. Candidates must demonstrate skills in creating Azure AI resources, deploying models, and integrating services into CI/CD pipelines while maintaining security.
Preparation tips
Focus on mastering Azure AI resource creation, CI/CD integration, and Responsible AI principles like content filtering and safety monitoring.
Implement generative AI solutions
Focuses on building generative AI solutions using Azure OpenAI and Microsoft Foundry. Key topics include deploying models, implementing prompt flow, applying RAG for grounding models in data, and fine-tuning models while optimizing performance and resource consumption.
Preparation tips
Practice deploying and fine-tuning Azure OpenAI models, implementing RAG patterns, and using prompt engineering techniques.
Implement an agentic solution
This domain covers the creation of custom agents and multi-agent workflows using the Microsoft Agent Framework and Foundry Agent Service. It includes understanding agent roles, designing complex autonomous workflows, and testing, optimizing, and deploying agentic solutions.
Preparation tips
Study agent roles, multi-agent orchestration, and the Microsoft Agent Framework for building autonomous workflows.
Implement computer vision solutions
Involves analyzing images and videos using Azure Vision and Video Indexer. Candidates must be able to perform image tagging, object detection, OCR, and spatial analysis, as well as train, evaluate, and publish custom vision models for classification and detection.
Preparation tips
Gain hands-on experience with image analysis, custom vision model training, OCR, and using Video Indexer for extracting insights.
Implement natural language processing solutions
Covers text analysis, translation, and speech processing using Azure Speech and Translator. Includes building custom language models, question-answering projects, and multi-turn conversations while handling PII, sentiment analysis, and intent recognition.
Preparation tips
Review text analysis, speech-to-text integration, and the creation of custom language and question-answering models.
Implement knowledge mining and information extraction solutions
Focuses on Azure AI Search, Document Intelligence, and Content Understanding. Skills include creating indexes and skillsets, extracting data using prebuilt or custom models, and implementing vector and semantic search solutions for efficient information retrieval.
Preparation tips
Understand indexing and querying in Azure AI Search, and practice extracting data using Document Intelligence and Content Understanding tools.