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Coursera

Market Forecasting with AI Demand Intelligence

via Coursera

Overview

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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.

Syllabus

  • Foundations and Applications of AI Demand Intelligence
    • Analyze how AI demand intelligence combines high-frequency data, external market signals, machine learning, and real-time demand sensing to improve forecasting across retail, manufacturing, energy, and finance.
  • Intelligent Infrastructure and Future-Ready Demand Planning
    • Develop scalable demand intelligence strategies using cloud infrastructure, MLOps, model governance, demand shaping, digital twins, generative AI, knowledge graphs, and autonomous AI agents.

Taught by

TSV Learning

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