AI-Powered Inventory Management: Forecasting and Smart Replenishment

Inventory is one of the largest working capital commitments in most businesses, and getting it wrong is expensive in both directions. Hold too much and you tie up cash; hold too little and you lose sales and trust. AI does not magically fix inventory, but it does change the quality of forecasts and the speed of response in ways that matter. This course gives you a calm, structured introduction. You will learn the building blocks of modern inventory management, where AI fits in, and how it changes traditional rules of thumb. The course stays grounded in widely used concepts including safety stock, economic order quantity, and ABC analysis. What you'll learn: - Understand the core inventory concepts including safety stock, EOQ, ABC analysis, and service level - Recognize the difference between traditional rules-based replenishment and AI-driven approaches - Explore the role of demand forecasting models including time series, machine learning, and hybrid methods - Identify the data inputs that matter, including sales history, promotions, lead times, and seasonality - Read the typical metrics used to evaluate inventory performance, including turns and fill rate - Understand the integration points between AI forecasts, ERP systems, and human planners The course begins with the goals of inventory management, moves through the AI techniques that have become common in modern supply chains, and closes with the operational realities of running these systems alongside human planners. Written exercises help you connect each concept to a real product, business, or category. This course is designed for absolute beginners with no supply chain or AI background, including business students, software developers exploring operations, and operators of small ecommerce or wholesale businesses. No prerequisites are needed. The course explains every concept as it appears and respects the real-world constraints of running an inventory.