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microsoft learning site AI-102 Skills measured Publish a Machine Learning Experiment with Microsoft Azure Machine Learning Studio Process and translate speech with Azure Cognitive Speech Services
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-102
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Candidates should apprehend the examination topics before they begin of preparation. because it'll extremely facilitate them in touch the core. Our AI-102 exam dumps will include the following topics:
1. Analyze solution requirements (25-30%)
Recommend Cognitive Services APIs to meet business requirements
Map security requirements to tools, technologies, and processes
Select the software, services, and storage required to support a solution
2. Design AI solutions (40-45%)
Design solutions that include one or more pipelines
Design solutions that uses Cognitive Services
Design solutions that implement the Bot Framework
Design the compute infrastructure to support a solution
Design for data governance, compliance, integrity, and security
3. Implement and monitor AI solutions (25-30%)
Implement an AI workflow
Integrate AI services with solution components
Monitor and evaluate the AI environment
| Section | Weight | Objectives |
|---|---|---|
| Implement knowledge mining and information extraction solutions | 15-20% | - Build knowledge bases and search indexes - Ingest and process structured/unstructured data - Implement intelligent search and retrieval - Extract entities, relationships, and key phrases |
| Implement natural language processing solutions | 15-20% | - Implement translation and summarization - Customize and deploy NLP models - Perform text analysis, sentiment detection, and language detection - Build conversational AI and chatbots |
| Implement generative AI solutions | 15-20% | - Implement model monitoring and feedback - Deploy and manage generative models - Orchestrate multiple models and containers - Integrate Azure OpenAI and other generative models - Apply prompt engineering and fine-tuning |
| Implement an agentic solution | 5-10% | - Test, deploy, and optimize agents - Understand agent use cases and types - Develop multi-agent workflows and orchestration - Build agents with Microsoft Foundry Agent Service |
| Plan and manage an Azure AI solution | 20-25% | - Select suitable AI models - Monitor, optimize, and secure AI solutions - Plan solutions aligned with responsible AI principles - Create and configure Azure AI resources - Select appropriate Microsoft Foundry Services - Choose services for generative AI, computer vision, NLP, speech, information extraction, knowledge mining |
| Implement computer vision solutions | 10-15% | - Integrate vision capabilities into applications - Build and deploy custom vision models - Process and index video content - Analyze images and detect objects/features - Extract text and handwriting from images |
Designing and Implementing a Microsoft Azure AI Solution
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