Supply Chain Analytics

About

Supply chains are complex systems involving multiple businesses and organizations with different goals and objectives. Many different analytical methods and techniques are used by researchers and practitioners alike to better design and manage their supply chains. This business and management course introduces the primary methods and tools that you will encounter in your study and practice of supply chains. We focus on the application of these methods, not necessarily the theoretical underpinnings.

We will begin with an overview of introductory probability and decision analysis to ensure that students understand how uncertainty can be modeled. Next, we will move into basic statistics and regression. Finally, we will introduce optimization modeling from unconstrained to linear, non-linear, and mixed integer linear programming.

This is a hands-on course. Students will use spreadsheets extensively to apply these techniques and approaches in case studies drawn from actual supply chains.

SC0x is different from our other courses as it is self-paced and has a scheduled final exam. All material is made available during the second week, allowing learners to begin with any topic at their own convenience.

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Unlock the core methodologies essential for supply chain analysis and modeling with the "Supply Chain Analytics" course, a foundational offering in the Data Science & AI domain. This course, provided by edX and part of the esteemed MITx Supply Chain Management MicroMasters Credential, is designed to equip learners with vital skills in statistics, regression, optimization, and probability. Guided by expert instructors from MIT, the course promises a deep dive into the analytical techniques that drive efficient supply chain management. Suitable for beginners, the course is available through flexible subscription options, including Starter and Professional plans, making it accessible to a broad audience eager to enhance their analytical prowess and advance their careers in supply chain management.