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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-infrastructure-basics-on-aws-no-labs-no-config/
课程评论：没有评论
AWS 上的 AI 基础设施基础（无实验，无配置）课程简介： 这门课程为希望了解云基础设施如何支持亚马逊网络服务（AWS）上的人工智能（AI）工作负载的人们提供了一个全面、非技术性的概述。本课程非常适合那些希望理解 AI 基础设施基础元素，同时又不想深入学习实际配置或实验操作的学习者。 在本课程中，您将了解： * **AI 的重要性：** 认识到 AI 在当今数字经济中的关键作用，以及它如何改变各行各业。 * **AI 基础设施的概念：** 了解支撑 AI 的云组件，包括数据、计算、存储和网络如何在 AWS 上协同工作。 * **核心 AWS 服务：** 重点介绍 EC2、S3、SageMaker、EFS 等关键 AWS 服务，以及它们在 AI 场景中的作用和优势。 * **关键基础设施概念：** 探讨可扩展、弹性、成本效益以及托管服务在加速 AI 开发中的作用。 * **目标受众：** 适用于商业领袖、项目经理、产品负责人、技术战略师、有抱负的 AI 从业者以及任何对云平台如何支持 AI 革命感兴趣的人。无需技术背景，只需了解如何在云中构建和扩展 AI 解决方案的愿望。 * **学习成果：** 学习结束后，您将具备进行 AI/云对话、参与战略规划以及在与技术团队合作时做出明智决策的词汇、背景知识和信心。您还将了解 AI 基础设施的发展趋势，如无服务器计算、基础模型和更自动化的 MLOps 流程。 * **职业机会：** 了解 AWS 上的 AI 基础设施将为您在日益增长的 AI 领域提供就业机会，无论您是计划领导团队、投资 AI 工具，还是继续深入学习。 该课程专注于清晰和易于理解，通过省略实际操作，让学习者能够专注于掌握核心概念和 AWS 服务。
The AI Infrastructure Basics on AWS (No Labs, No Config) course provides a comprehensive, non-technical overview of how cloud infrastructure supports artificial intelligence workloads on Amazon Web Services (AWS). This course is ideal for anyone looking to understand the foundational elements of AI infrastructure without getting involved in hands-on configuration or lab work.In today's digital economy, AI is no longer optional-it's essential. From powering recommendations and chatbots to automating workflows and enabling predictive analytics, AI is transforming industries. But before building models or deploying applications, it's crucial to understand the infrastructure that makes AI possible. This course demystifies the cloud components that support AI, helping you see the bigger picture of how data, compute, storage, and networking come together on AWS.One of the key advantages of this course is its focus on clarity and accessibility. By removing the complexity of labs and configurations, learners can concentrate on understanding core AWS services like EC2, S3, SageMaker, EFS, and more-how they work together, when to use them, and why they matter for AI. You'll also explore key concepts like scalability, elasticity, cost-efficiency, and the role of managed services in accelerating AI development.This course is designed for a broad audience: business leaders, project managers, product owners, tech strategists, aspiring AI practitioners, and anyone curious about how cloud platforms like AWS support the AI revolution. You don't need a technical background-just a desire to understand how AI solutions are built and scaled in the cloud.By the end of this course, you'll be equipped with the vocabulary, context, and confidence to engage in AI/cloud conversations, participate in strategic planning, and make informed decisions when working with technical teams. You'll also gain insight into the evolving landscape of AI infrastructure, including trends like serverless computing, foundation models, and the shift toward more automated MLOps pipelines.As AI adoption continues to grow, so will the demand for professionals who can bridge the gap between business goals and technical execution. Understanding AI infrastructure on AWS will position you for future opportunities-whether you're planning to lead a team, invest in AI tools, or continue your learning with more advanced hands-on courses.
