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AI-102T00: Designing and Implementing a Microsoft Azure AI Solution

The AI-102T00: Designing and Implementing a Microsoft Azure AI Solution course was designed to equip developers and AI professionals with the skills required to build, deploy, integrate, and manage artificial intelligence solutions on Microsoft Azure. The training covered key Azure AI capabilities, including Azure AI services, computer vision, natural language processing, speech, knowledge mining, document intelligence, and generative AI. Participants learned how to select appropriate Azure AI services, integrate AI capabilities into applications, secure AI solutions, and monitor AI workloads. Through practical, development-focused learning, participants gained experience working with Azure AI Vision, Azure AI Language, Azure AI Speech, Azure AI Search, Azure AI Document Intelligence, Azure OpenAI, and Azure AI services. The course also addressed responsible AI considerations and techniques for implementing AI solutions using Azure SDKs and APIs. The course was intended for developers and AI professionals who wanted to build practical AI applications and solutions on Azure. The original AI-102 skills outline covered planning and managing Azure AI solutions, decision-support solutions, computer vision, natural language processing, knowledge mining and document intelligence, and generative AI.
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Course Description

Course Module

Module 1: Plan and Manage an Azure AI Solution

  • Azure AI solution planning
  • Selecting appropriate Azure AI services
  • AI solution architecture
  • Azure AI resources
  • Authentication and authorization
  • Secure AI solution development
  • Monitoring AI solutions
  • Responsible AI principles
  • Cost and performance considerations

Module 2: Implement Decision-Support Solutions

  • Azure AI Vision
  • Image analysis
  • Image classification
  • Object detection
  • Optical character recognition (OCR)
  • Face-related capabilities
  • Custom Vision solutions
  • Video analysis
  • Azure AI Content Safety

Module 3: Implement Azure AI Vision Solutions

  • Image analysis
  • Image classification
  • Object detection
  • Optical character recognition
  • Face detection and analysis
  • Custom Vision
  • Image and video processing
  • Azure AI Vision SDKs and APIs

Module 4: Implement Natural Language Processing Solutions

  • Azure AI Language
  • Text analysis
  • Sentiment analysis
  • Key phrase extraction
  • Named entity recognition
  • Custom text classification
  • Question answering
  • Conversational language understanding
  • Azure AI Speech
  • Speech recognition
  • Speech synthesis
  • Speech translation

Module 5: Implement Knowledge Mining and Document Intelligence Solutions

  • Azure AI Search
  • Search indexes
  • Indexers
  • Data sources
  • Skillsets
  • Semantic search
  • Vector search
  • Knowledge mining
  • Azure AI Document Intelligence
  • Prebuilt models
  • Custom document models
  • Information extraction
  • OCR and document analysis

Module 6: Implement Generative AI Solutions

  • Azure OpenAI
  • Generative AI fundamentals
  • Generative AI models
  • Prompt engineering
  • Azure OpenAI APIs
  • Chat completion
  • Embeddings
  • Retrieval-augmented generation concepts
  • Responsible generative AI
  • Generative AI application integration
Who should attend
  • AI Engineers
  • Azure AI Developers
  • Software Developers
  • Cloud Developers
  • Machine Learning Professionals
  • Data Scientists
  • Application Developers
  • AI Solution Developers
  • Cloud Engineers
  • Software Engineers working with AI applications
  • Professionals integrating AI capabilities into Azure applications
  • Developers looking to build expertise in Azure AI services and generative AI
Key Takeaways
  • Understand how to plan and manage Azure AI solutions.
  • Select appropriate Azure AI services and resources for different business requirements.
  • Implement computer vision solutions for image and video analysis.
  • Develop solutions using Azure AI Language for text analysis and natural language processing.
  • Implement speech recognition, synthesis, and translation solutions.
  • Build knowledge-mining solutions using Azure AI Search.
  • Extract information from documents using Azure AI Document Intelligence.
  • Develop generative AI applications using Azure OpenAI.
  • Work with Azure AI SDKs, REST APIs, and development tools.
  • Implement authentication, security, monitoring, and responsible AI practices.
  • Integrate AI capabilities into cloud-based applications and business solutions.
  • Develop practical skills for designing and implementing AI-powered Azure solutions.
Preqrequisites
  • Experience with software development and programming.
  • Familiarity with Microsoft Azure and cloud computing concepts.
  • Working knowledge of Python or C#.
  • Experience using REST APIs and SDKs.
  • Basic understanding of JSON and HTTP-based services.
  • Familiarity with Azure Portal and Azure resources.
  • Basic understanding of artificial intelligence and machine learning concepts.
  • Familiarity with application development, authentication, and security concepts.

Exam: AI-102: Designing and Implementing a Microsoft Azure AI Solution
Former Passing Score: 700 or greater

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FAQs

What was the AI-102T00: Designing and Implementing a Microsoft Azure AI Solution Course?

AI-102T00 was a Microsoft intermediate-level training course designed to help developers build and implement AI solutions on Microsoft Azure. It covered computer vision, natural language processing, speech, knowledge mining, document intelligence, and generative AI.

What topics were covered in AI-102 Azure AI Training?

The course covered Azure AI services, Azure AI Vision, Azure AI Language, Azure AI Speech, Azure AI Search, Azure AI Document Intelligence, Azure OpenAI, computer vision, NLP, knowledge mining, and generative AI.

What programming knowledge was recommended for AI-102?

Learners were expected to have software development experience and familiarity with Python or C#, REST APIs, SDKs, JSON, and Azure development concepts. Programming experience was particularly important because the course focused on implementing AI capabilities within applications.

What certification was associated with AI-102?

AI-102 was the examination associated with the Microsoft Certified: Azure AI Engineer Associate certification. However, both the certification and examination retired on June 30, 2026.

What is the replacement for AI-102T00?

Microsoft retired AI-102T00 and lists AI-103T00: Develop AI apps and agents on Azure as its replacement course. The newer AI-103 pathway focuses on developing AI applications and agents, including generative AI, agentic solutions, computer vision, text analysis, and information extraction.

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