AI-102 exam dumps

Microsoft AI-102 Value Package

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  • Exam Code: AI-102
  • Exam Name: Designing and Implementing a Microsoft Azure AI Solution
  • No. of Questions: 425 Questions and Answers
  • Updated: Jul 30, 2026

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To prepare for the AI-102 certification exam, candidates need to have a strong understanding of machine learning algorithms, data analysis and visualization, and cloud computing technologies. They also need to have a deep understanding of the Azure platform and its various services, including Azure Cognitive Services, Azure Machine Learning, and Azure Databricks.

To prepare for the AI-102 certification exam, you should have a solid understanding of Azure fundamentals and AI concepts. You should also have experience in developing and implementing AI solutions using Azure services such as Azure Machine Learning, Azure Databricks, and Azure Bot Service.

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

How to Register For Exam AI-102: Designing and Implementing a Microsoft Azure AI Solution?

Exam Register Link: https://examregistration.microsoft.com/?locale=en-us&examcode=AI-102&examname=Exam%20AI-102:%20Designing%20and%20Implementing%20a%20Microsoft%20Azure%20AI%20Solution&returnToLearningUrl=https%3A%2F%2Fdocs.microsoft.com%2Flearn%2Fcertifications%2Fexams%2Fai-102

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Microsoft AI-102 Exam Syllabus Topics:

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

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