Detailed Course Information |
Fall 2024
Sep 19, 2024 |
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| LOG 3253P - SC Optim Prescript Analytics |
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As the capstone in the Supply Chain Analytics Professional Certificate program, this course combines advanced analytics and mathematical optimization to find solutions for supply chain problems. You’ll learn various techniques, such as linear programming, mixed integer programming, and heuristics, with a focus on production processes, distribution network optimization, and routing. You’ll learn how to make data-driven decisions based on prescriptive analytics along with best practices for implementing optimization applications. Using the fictional Cardboard Company (CBC) case study, you’ll create production plans that maximize profit, use heuristics to make effective routing decisions, and prescribe ways to reduce costs throughout the supply chain.
While you are not required to complete the Transforming Supply Chain Management and Performance Analysis, Creating Business Value with Statistical Analysis, and Machine Learning Applications for Supply Chain Planning courses prior to this capstone, we suggest you being familiar with their learning outcomes.
Recommended Prerequisites:
General supply chain management knowledge
LOG 3250P - Transforming Supply Chain Management and Performance Analysis
LOG 3251P - Creating Business Value with Statistical Analysis
LOG 3252P - Machine Learning Applications for Supply Chain Planning
Required Prerequisites:
Elementary knowledge of statistics
Basic coding skills
Experience using Python, Power BI, and Microsoft Azure
1.400 Continuing Education Units 14.000 Lecture hours Syllabus Available Grade Basis: Z Logistics Institute Division Professional Education Department Course Attributes: Supply Chain Mgt, Sply Chn Analytics Prof, PE GT Account Creation Needed, PE Canvas Section, PE IDMgt Account Activat Email |
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