AI Product Manager
Three tracks in sequence: ML & AI Engineering, then AI Product Management, then Responsible AI Engineering. The engineering comes first on purpose: the point is to be a product person who can tell a hard technical constraint from a soft one.
3 courses · Intermediate
The path, in order
- ML & AI Engineering — From Python basics to production ML and AI systems
- AI Product Management — Ship AI features people actually trust, from opportunity to launch
- Responsible AI Engineering — Build a deployable AI audit toolkit: bias detection, explainability, privacy and governance in one pipeline
Optional foundations, if you are starting from zero
The path assumes you can already write Python. If you cannot, take these first.
- Programming & CS Foundations — How to think like a programmer, from zero, before any AI or math content
- Data Analysis & Visualization — pandas, NumPy, and the daily skill of turning real messy data into an answer
What you become
A product manager who understands the engineering well enough to scope it, and who can write the governance and evaluation criteria an AI feature ships against.
Roles this path prepares you for
- AI Product Manager
- AI Program Manager
- Responsible AI Lead
- AI Strategy Consultant
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