A complete, exam-focused guide to managing AI projects using data-centric, real-world project management practices
Sub Category
- Project Management
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Objectives
- Understand the CPMAI methodology and how it differs from traditional project management
- Explain why AI projects fail and how to prevent common failure patterns
- Define AI project scope in environments with uncertainty and learning
- Assess AI feasibility and risk before major investments
- Evaluate data readiness, data quality, and ground truth
- Manage data labeling, pipelines, and quality controls
- Align AI initiatives with business value and ROI
- Select the right AI pattern for different business problems
- Apply AI-specific metrics across the project lifecycle
- Make Go / No-Go decisions using data-driven criteria
Pre Requisites
- Basic understanding of project management concepts
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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