Learn how AI demand sensing and market forecasting help organizations anticipate market shifts, improve demand predictions, and make data-driven supply chain decisions.

Designed for supply chain professionals, demand planners, analysts, and business decision-makers, this course explores how machine learning and real-time demand signals enhance forecasting, inventory planning, and operational efficiency. You'll examine how macroeconomic indicators, climate conditions, regulatory developments, and alternative data influence consumer and industrial demand. Learn to evaluate AI forecasting techniques, SKU-level predictions, probabilistic forecasting, and advanced time-series analysis. Explore MLOps workflows and cloud-edge architectures that support scalable AI forecasting systems. Discover how predictive analytics improves inventory management and replenishment across retail, consumer goods, manufacturing, and logistics. You'll also assess organizational adoption, implementation strategies, performance measurement, and AI governance practices. By the end of this course, you'll be able to interpret complex demand signals, evaluate AI-driven forecasting models, assess industry applications, and recommend improvements to supply chain decisions. What makes this course distinctive is its integrated focus on market drivers, advanced forecasting, scalable architectures, and business adoption, connecting AI demand sensing with practical operational decisions.