Lead and Evaluate AI Project Implementations

Coursera MOOC / Non-credit USD 49
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Lead and Evaluate AI Project Implementations

About this course

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.

What you'll learn

  • understand obstacles in AI project execution
  • coordinate project workstreams using implementation playbooks
  • validate deliverables through quality assurance and acceptance testing

Course objectives

  • avoid common pitfalls in AI project management
  • ensure alignment among project teams
  • deliver AI projects that meet quality standards

Skills you'll gain

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