DSCI 452 Application of AI in Supply Chain Management
This course explores the application of artificial intelligence (AI) and machine learning (ML) techniques within the context of supply chain management (SCM). It is designed for business managers and undergraduate students with limited programming experience, offering a practical introduction to AI and ML applications in solving real-world supply chain problems. Throughout the course, students will learn how to apply AI and ML models for tasks such as demand forecasting, inventory optimization, and predictive maintenance. The course balances theoretical understanding with hands-on experience using real-world datasets, and no prior programming background is required, though familiarity with programming may be helpful. By the end of the course, students will have a solid foundation in both the theoretical concepts and practical applications of AI and ML in SCM.
Prerequisites
4 Undergraduate credits
Effective May 6, 2025 to present
Learning outcomes
General
- Apply machine learning models to optimize SCM processes, including demand forecasting, supplier selection, and risk mitigation.
- Analyze the effectiveness of deep learning techniques, such as neural networks and LSTMs, in addressing complex SCM problems.
- Design and implement digital twin models to optimize inventory management and simulate supply chain processes.
- Develop AI-driven SCM solutions using real-world datasets, demonstrating the ability to interpret and apply data-driven insights.
- Critically assess emerging AI tools and trends to provide strategic insights for supply chain innovation and decision-making.
Fall 2025
| Section | Title | Instructor | books | eservices |
|---|---|---|---|---|
| 50 | Application of AI in Supply Chain Management | Luo, Charles Changyue | Books for DSCI-452-50 Fall 2025 | Course details for DSCI-452-50 Fall 2025 |