Build practical skills in AI demand intelligence and market forecasting to anticipate demand shifts, improve planning, and respond to volatile markets. Designed for demand planners, analysts, supply chain professionals, and business leaders, this course shows you how modern demand intelligence combines high-frequency data, economic indicators, weather patterns, customer sentiment, and competitive signals with real-time demand sensing.

You’ll analyze nonlinear demand drivers and evaluate machine learning forecasting methods, including LSTMs, transformers, probabilistic forecasting, and quantile regression. You’ll explore applications across retail, manufacturing, energy, and financial services while examining feature stores, cloud infrastructure, forecast bias, concept drift, performance metrics, model monitoring, and responsible data governance. You’ll also apply demand-shaping methods and develop scalable demand intelligence strategies using MLOps, digital twins, generative AI, knowledge graphs, and agentic AI. By the end, you’ll be able to connect AI-driven forecasts with inventory, capacity, pricing, sustainability, revenue, and risk decisions. The course uniquely connects forecasting methods, real-time market signals, intelligent infrastructure, and future-ready AI planning in one practical framework.