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If you are looking to demonstrate your skills in designing and implementing Microsoft Azure AI solutions, then the Microsoft AI-102: Designing and Implementing a Microsoft Azure AI Solution exam is the right choice for you. AI-102 exam covers all the essential topics related to designing and implementing AI solutions using Azure services and tools. Passing AI-102 exam will help you earn the Microsoft Certified: Azure AI Engineer Associate certification, which is highly valued by employers and recognized globally.

Skills measured

  • Implement knowledge mining solutions (15-20%)
  • Plan and manage an Azure Cognitive Services solution (15-20%)
  • Implement Computer Vision solutions (20-25%)
  • Implement natural language processing solutions (20-25%)
  • Implement conversational AI solutions (15-20%)

The AI-102 certification exam covers a wide range of topics related to AI, including natural language processing, computer vision, speech recognition, and machine learning. AI-102 exam also covers the use of various tools and technologies that are commonly used in the development and deployment of AI solutions on the Azure platform. These tools include Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service.

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

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Microsoft AI-102 (Designing and Implementing a Microsoft Azure AI Solution) Certification Exam is a highly recognized and sought-after certification for professionals who are interested in AI and want to work with Azure AI solutions. Designing and Implementing a Microsoft Azure AI Solution certification exam is designed to test the knowledge and skills required to design and implement AI solutions using Azure services. It is an advanced level exam that requires the candidate to have a deep understanding of AI and Azure services.

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Microsoft AI-102 Exam Syllabus Topics:

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

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