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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-100-designing-and-implementing-an-azure-ai-solution/
课程评论：没有评论
课程名称：AI-100：设计和实施Azure AI解决方案 课程概述：本课程最初是针对AI-100考试设计的，但学习者在准备AI-102时仍可以从现有模块中受益，因为核心概念和实用知识依然高度相关。微软Azure提供了一整套服务，旨在实现智能AI驱动解决方案的快速开发、部署和运营。本课程将帮助您了解这些服务如何整合，以支持AI应用在真实场景中的设计、实施、监控、优化和安全性。尽管课程最初是为AI-100认证考试而设，但内容仍然对追求AI-102的学习者非常有价值，涵盖了在不断发展的Azure AI领域中成功所需的基础和高级主题。 您将学到的内容：课程深入探讨Azure认知服务API，包括： - 视觉API：人脸检测、内容标签和光学字符识别（OCR） - 语言API：语言检测、情感分析和关键词提取 您将使用Python和JavaScript实现这些服务，确保获得实际的、现实世界的学习体验，为现代AI开发任务做好准备。 详细课程内容： 1. 分析解决方案需求（25-30%） - 推荐和选择Azure认知服务API - 选择合适的数据处理技术和AI模型 - 将安全性和自动化需求映射到技术和工具 - 符合数据隐私、保护和合规法规 - 确定支持AI解决方案的软件、服务和存储 2. 设计AI解决方案（40-45%） - 创建AI工作流程和数据采集/输出策略 - 使用Azure机器学习和AI应用集成管道 - 使用视觉、语音、语言和知识API构建解决方案 - 使用Microsoft Bot Framework和LUIS设计和集成机器人 - 选择合适的计算基础设施（GPU、FPGA、CPU）并确保成本效益 - 在AI设计中融入治理、合规和安全原则 3. 实施和监控AI解决方案（25-30%） - 开发和管理AI管道和数据流 - 构建自定义AI服务接口和解决方案端点 - 集成Azure认知服务和Microsoft Bot Framework - 实施Azure认知搜索 - 监控关键性能指标并优化AI性能 无论您是想通过AI-102认证，还是希望在组织中应用AI概念，本课程将为您提供理论理解和实践专业知识。如果您有任何问题或需要指导，请随时与我联系。我会支持您的学习旅程。欢迎参加课程——让我们开始吧！
Course Update:While the original content is based on the AI-100 exam, learners preparing for AI-102 can still benefit from the existing modules, as the core concepts and practical knowledge remain highly relevant and applicable to the updated certification.Course Overview:Microsoft Azure provides a comprehensive suite of services designed to enable rapid development, deployment, and operationalization of intelligent AI-driven solutions. This course is structured to help you understand how these services integrate to support the design, implementation, monitoring, optimization, and security of AI applications in real-world scenarios.Originally tailored for the Microsoft AI-100 certification exam, the course remains highly valuable for those pursuing AI-102, as it covers the foundational and advanced topics that are critical to success in the evolving AI landscape on Azure.What You'll Learn:The course offers deep, hands-on exploration of Azure Cognitive Services APIs, including:Vision APIs: Face detection, content tagging, and Optical Character Recognition (OCR)Language APIs: Language detection, sentiment analysis, and key phrase extractionYou'll implement these services using both Python and JavaScript, ensuring a practical, real-world learning experience that prepares you for modern AI development tasks.Detailed Course Content:1. Analyze Solution Requirements (25-30%)Recommend and select Azure Cognitive Services APIsChoose appropriate data processing technologies and AI modelsMap security and automation needs to technologies and toolsAlign with data privacy, protection, and compliance regulationsIdentify software, services, and storage to support the AI solution2. Design AI Solutions (40-45%)Create AI workflows and data ingestion/egress strategiesIntegrate pipelines using Azure Machine Learning and AI appsBuild solutions using Vision, Speech, Language, and Knowledge APIsDesign and integrate bots using the Microsoft Bot Framework and LUISSelect the right compute infrastructure (GPU, FPGA, CPU) and ensure cost-efficiencyIncorporate governance, compliance, and security principles in AI design3. Implement and Monitor AI Solutions (25-30%)Develop and manage AI pipelines and data flowConstruct custom AI service interfaces and solution endpointsIntegrate Azure Cognitive Services and the Microsoft Bot FrameworkImplement Azure Cognitive SearchMonitor key performance metrics and optimize AI performanceWhether you are aiming to pass the AI-102 certification or seeking to apply AI concepts in your organization, this course will equip you with both theoretical understanding and practical expertise.If you have any questions or need guidance, feel free to reach out. I'm here to support your learning journey.Welcome to the course - let's get started!
