AI Product Management

Machine learning literacy for people who ship products

This Specialization doesn't teach you to write production ML code — it teaches you to understand what's actually happening inside a model well enough to make good decisions about it. That's a different, and often harder, skill than either pure engineering or pure management, and it's aimed squarely at the gap between the two.

You'll work through the core toolkit of applied machine learning: supervised and unsupervised learning, regression and logistic regression, decision trees, and artificial neural networks, alongside model evaluation and training concepts that let you judge whether a model is actually good, not just impressive-sounding.

• How different ML algorithm families work and when each applies
• Evaluating and comparing model performance
• Predictive analytics for business forecasting
• Translating model outputs into product decisions

Pitched at a beginner level despite the technical depth of the topics, it's designed for product managers, analysts, and career-changers rather than working data scientists. Over 63,000 learners have taken it, making it one of the more established starting points for anyone who needs to talk credibly about ML without building it themselves.