Artificial intelligence (AI) projects are some of the most exciting and fast-moving initiatives in today’s organizations. But while AI systems can fail because of technical problems, in practice they often fail for another reason: poor execution. Blockers aren’t tracked, responsibilities blur, teams lose alignment, or deliverables don’t meet the quality standards promised to stakeholders.

Lead and Evaluate AI Project Implementations
访问权限由 Coursera Learning Team 提供
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书

该课程共有1个模块
Artificial intelligence (AI) projects are some of the most exciting and fast-moving initiatives in today’s organizations. But while AI systems can fail because of technical problems, in practice, they often fail for another reason: poor execution. Blockers aren’t tracked, responsibilities blur, teams lose alignment, or deliverables don’t meet the quality standards promised to stakeholders. This course, AI Project Implementation: Playbooks, QA, and Readiness, is designed to help you avoid those pitfalls. It focuses on two practical skills that every project manager and program lead needs: coordinating project workstreams with implementation playbooks and validating deliverables through quality assurance (QA) and acceptance testing. Together, these skills ensure that AI projects don’t just get built—they get delivered in a way that is reliable, accountable, and ready for real-world deployment.
涵盖的内容
6个视频2篇阅读材料3个作业
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
位教师

提供方
人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.
从 Business 浏览更多内容

Johns Hopkins University
¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。






