Artificial Intelligence Fundamentals for Supply Chain Management

Catalog description

Artificial Intelligence (AI) is transforming how companies manage their supply chains, enabling more accurate predictions, smarter decisions, increased efficiency, and competitive advantage. This course provides a comprehensive introduction to AI and Machine Learning (ML), emphasizing practical applications within Supply Chain Management (SCM). Starting with fundamental AI concepts, students explore supervised and unsupervised learning methods, including decision trees, ensemble learning, clustering, and dimensionality reduction, through practical SCM use cases. Building upon this foundation, the course covers advanced deep learning methods, including multi-layer perceptrons (MLPs), convolutional neural networks (CNNs) for computer vision, and recurrent neural networks (RNNs) and transformers for natural language processing (NLP), relevant to inventory management, predictive maintenance, quality control, and supplier analysis. The course also addresses critical topics in AI ethics, model interpretability, fairness, and bias mitigation, promoting responsible AI implementation. Through lectures and practical examples, students will develop skills to implement and critically assess AI-driven solutions to enhance supply chain prediction, decision-making, and performance. Coding exercises will be done in Python. Prereq: SCMG 433 and SCMG 492 and enrolled in the Master of Supply Chain Management program.