Supply Chain Analytics is a transformative approach that replaces guesswork with data-driven decision making. A crucial tool in this field is optimization analysis, which aids in making informed choices. According to Deloitte, organizations with highly efficient supply chains experience significantly above-average revenue growth, with a staggering 79% achieving this feat. In this course, you will be introduced to PuLP, a Python-based Linear Program optimization modeler. Through PuLP, you will learn how to effectively formulate and address optimization questions related to Supply Chain management. These questions may include determining the optimal location for a production facility or allocating production demand across multiple facilities. Furthermore, we will delve into the outcomes of these models and their implications through sensitivity and simulation testing. By leveraging the power of Python and PuLP, this course will equip you with the skills to enhance supply chain decision making. By completing this course, you will position yourself to make significant improvements in supply chain management and contribute to the overall success of your organization.