Outline

Grasp core AI/ML concepts essential for product management. • Explore various model types: Supervised, Unsupervised, and Generative AI. • Understand the critical data lifecycle and its product impact. • Analyze evaluation metrics and make informed trade-offs.

Outline

Identify compelling AI use cases with market potential. • Scope Minimum Viable Products (MVPs) for AI capabilities. • Manage data acquisition, labeling, and annotation processes. • Collaborate effectively with data scientists on model selection.

Outline

Design for explainability, trust, and user comprehension. • Implement Human-in-the-Loop (HITL) design patterns. • Establish robust feedback loops and active learning systems. • Address ethical considerations in AI interface design.

Outline

Master model deployment workflows and leverage essential tools. • Execute A/B testing and establish effective monitoring for AI systems. • Manage model drift, retraining, and continuous updates. • Integrate MLOps practices and select appropriate platform choices.

Outline

Develop a compelling AI product strategy aligned with business goals. • Create strategic roadmaps for data-driven product development. • Lead and manage cross-functional AI product teams. • Navigate legal, compliance, and risk frameworks in AI.