AI Product Management
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Module 1: What Changes When the Product Learns
Deterministic Software Versus Probabilistic Features
Preview
Deciding Whether a Problem Needs a Model at All
The AI Product Lifecycle
3 lessons
Module 2: Data Strategy for Product Managers
Assessing Data Readiness
Labeling Strategy and Ground Truth
Privacy, Consent, and Data Governance
3 lessons
Module 3: Working With Technical Teams
Translating Product Goals Into Model Objectives
Running Discovery and Experiments With Data Scientists
Build, Buy, or API: Sourcing the Model
3 lessons
Module 4: Designing the Experience
Designing for Uncertainty and Error
Building Trust and Setting Expectations
Feedback Loops That Improve the Product
3 lessons
Module 5: Evaluation, Launch, and Risk
Evaluation Before Launch: Offline, Shadow, and Limited Release
Monitoring and Managing Drift in Production
Responsible AI: Fairness, Safety, and Accountability
3 lessons
Module 6: Strategy and Leadership
Prioritizing an AI Roadmap
Communicating With Stakeholders and Executives
Building the Team and Your Continuing Development
3 lessons
Module 2: Data Strategy for Product Managers
Labeling Strategy and Ground Truth
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