AI & Analytics in Supply Chain

Catalog description

This course introduces the undergraduate-level quantitative theory and tools to remedy the supply chain management (SCM) crisis after the COVID-19 pandemic. Students from SCM major or related major in their junior or senior year are encouraged to take this interdisciplinary course covering techniques and knowledge from Microeconomics, Statistics, Operations Management, and Data Analytics (a brief review of the required knowledge in this field is scheduled before the introduction of modeling). Students will be exposed to analytical concepts and techniques, case studies, and recent examples in academia and industry. It covers the major issues and models practitioners concerning the related fields: inventory management, logistics management, SCM network design and planning, distribution strategies, qualitative and quantitative forecasting, data analytics, recent IT in SCM (e.g., AI, blockchain, Internet of Things, robotics), etc. Basic modeling and programming can be expected on the course. However, the teaching approaches, contents, difficulty levels, and final deliverables should seamlessly fit the expectations, backgrounds, and prior knowledge of students in each section.