AI for Everyone：《人人都能学的AI》

https://www.deeplearning.ai/courses/ai-for-everyone/

AI不仅仅适用于工程师。“人人皆可AI”是一个非技术性的课程，将帮助您理解AI技术，并发现将AI应用于您自己组织中的问题的机会。您将看到当今AI可以做的事情及其无法做到的事情的示例。最后，您将理解AI如何影响社会以及如何在这一技术变革中顺利航行。

如果您是非技术性的商务专业人士，“人人皆可AI”将帮助您了解如何建立可持续的AI战略。如果您是机器学习工程师或数据科学家，这是向您的经理、副总裁或首席执行官推荐的课程，以便让他们理解您能做什么（以及不能做什么！）。

AI is not only for engineers. “AI for Everyone”, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today’s AI can – and cannot – do. Finally, you will understand how AI is impacting society and how to navigate through this technological change.

If you are a non-technical business professional, “AI for Everyone” will help you understand how to build a sustainable AI strategy. If you are a machine learning engineer or data scientist, this is the course to ask your manager, VP or CEO to take if you want them to understand what you can (and cannot!) do.

AI不仅仅适用于工程师。“人人皆可AI”是一个非技术性的课程，将帮助您理解AI技术，并发现将AI应用于您自己组织中问题的机会。您将看到当今AI可以做的事情以及无法做到的事情的示例。最后，您将理解AI如何影响社会，以及如何在这一技术变革中顺利应对。

如果您是非技术性的商务专业人士，“人人皆可AI”将帮助您了解如何建立可持续的AI战略。如果您是机器学习工程师或数据科学家，这是您向经理、副总裁或首席执行官推荐的课程，以便让他们理解您能做什么（以及不能做什么！）。如果您希望您的组织在使用AI方面有所提升，这也是一个值得向每个人推荐的课程，尤其是您的非技术同事。

第1周：什么是AI

• 介绍
• 机器学习
• 什么是数据
• AI术语
• 什么造就了一家AI公司？
• 机器学习能做什么和不能做什么
• 深度学习的直观解释

第2周：构建AI项目

• 机器学习项目的工作流程
• 数据科学项目的工作流程
• 每个岗位都需要学习如何使用数据
• 如何选择AI项目
• 与AI团队合作
• AI团队的技术工具

第3周：公司中的AI

• 案例研究：智能音箱
• 案例研究：自动驾驶汽车
• AI团队的角色示例
• AI转型手册
• 避免AI的陷阱
• 开展AI的第一步
• 主要AI应用的调查
• 主要AI技术的调查

第4周：AI与社会

• AI的现实视角
• 歧视/偏见
• 对抗性攻击
• 不当用途
• AI与发展中国家
• AI与工作
• 结论

AI is not only for engineers. “AI for Everyone”, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today’s AI can – and cannot – do. Finally, you will understand how AI is impacting society and how to navigate through this technological change.

If you are a non-technical business professional, “AI for Everyone” will help you understand how to build a sustainable AI strategy. If you are a machine learning engineer or data scientist, this is the course to ask your manager, VP or CEO to take if you want them to understand what you can (and cannot!) do.
AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone – especially your non-technical colleagues – to take.

Week 1: What is AI

Introduction
Machine Learning
What is data
The terminology of AI
What makes an AI company?
What Machine Learning can and cannot do
Intuitive explanation of deep learning
Week 2: Building AI Projects

Workflow of a Machine Learning project
Workflow of a Data Science project
Every job function needs to learn to use data
How to choose an AI project
Working with an AI team
Technical tools for AI teams
Week 3: AI in Your Company

Case study: Smart speaker
Case study: Self-driving car
Example roles of an AI team
AI Transformation Playbook
AI pitfalls to avoid
Taking your first step in AI
Survey of major AI applications
Survey of major AI techniques
Week 4: AI and Society

A realistic view of AI
Discrimination / Bias
Adversarial attacks
Adverse uses
AI and developing nations
AI and jobs
Conclusion