AI learning path
Choose valuable AI problems, design trustworthy human-AI interactions, and connect experiments to measurable product and business outcomes.
For Product managers, founders, designers, and business leaders
6 resources
Google PAIR
A human-centered product guide covering user needs, data, mental models, explainability, feedback, control, and graceful failure in AI products.
Google Codelabs
A guided product exercise for applying human-centered data practices, explainability, and calibrated trust to an AI feature concept.
Microsoft Learn
A business-leader learning path on creating value, responsible adoption, organizational readiness, and scaling AI initiatives.
OpenAI Academy
A practical learning path for moving from individual prompts to repeatable workflows, review habits, and useful applications of AI at work.
Duke University · Jon Reifschneider
A non-coding specialization on machine-learning foundations, project leadership, data processes, human-centered design, privacy, and ethical AI product decisions.
Stanford Institute for Human-Centered AI
A globally sourced report on AI research, technical performance, adoption, investment, responsible AI, public opinion, education, policy, and societal impact.
