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Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution

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

Download exam skills outline

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102

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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.

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Microsoft AI-102 Exam Syllabus Topics:

SectionWeightObjectives
Implement generative AI solutions15-20%- Deploy and manage generative models
- Implement model monitoring and feedback
- Orchestrate multiple models and containers
- Apply prompt engineering and fine-tuning
- Integrate Azure OpenAI and other generative models
Implement natural language processing solutions15-20%- Perform text analysis, sentiment detection, and language detection
- Customize and deploy NLP models
- Implement translation and summarization
- Build conversational AI and chatbots
Implement knowledge mining and information extraction solutions15-20%- Ingest and process structured/unstructured data
- Extract entities, relationships, and key phrases
- Build knowledge bases and search indexes
- Implement intelligent search and retrieval
Implement an agentic solution5-10%- Understand agent use cases and types
- Develop multi-agent workflows and orchestration
- Test, deploy, and optimize agents
- Build agents with Microsoft Foundry Agent Service
Plan and manage an Azure AI solution20-25%- 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
- Select appropriate Microsoft Foundry Services
Implement computer vision solutions10-15%- Process and index video content
- Build and deploy custom vision models
- Integrate vision capabilities into applications
- Analyze images and detect objects/features
- Extract text and handwriting from images

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