Who Should Attend?
Experienced professionals who want to improve their SCM processes using analytics and/or want to learn how to grow/develop analytics projects in their operations organization.
About the Program
The program consists of four courses:
- Transforming Supply Chain Management and Performance Analysis
- Creating Business Value with Statistical Analysis
- Machine Learning Applications for Supply Chain Planning
- Supply Chain Optimization.
Each course moves along the analytics continuum from dashboarding and data visualization to machine learning and optimization.
Take all four courses in the Supply Chain Analytics Professional (SCA) series within four years to receive your certificate. Classes can be taken in any order to complete the program.
Course Descriptions
• Course 1: Transforming Supply Chain Management and Performance Analysis
This course prepares you to apply leading-edge analytical methods and technology enablers across the supply chain. Learn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, discover data cleansing, exploratory data analysis, and visualization. Use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data before seeing how to gather, analyze, and prepare your data through descriptive analytics. Discuss the causes of underperformance and to build dashboards to visualize supply chain data before seeing how to gather, analyze, and prepare your data through descriptive analytics.
Next Class Date:
Course 1 has been completed for 2024.
Contact us for class dates in 2025.
⊕ Learn more about Course 1
• Course 2: Creating Business Value with Statistical Analysis
This course is the second in the four-course Supply Chain Analytics Professional certificate program. It emphasizes operational performance metrics to align supply chain management with strategic business goals. Learn several statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) along with inventory management models. Use diagnostic analytics with PowerBI and Python to conduct demand and service profiling, undertake root cause analysis, and use time series forecasting in inventory management.
Note: Knowledge of content and ability to apply skills covered in Course 1 of the program is beneficial but not required to take Course 2.
Next Class Date:
Course 2 has been completed for 2024.
Contact us for class dates in 2025.
⊕ Learn more about Course 2
• Course 3: Machine Learning Applications for Supply Chain Planning
This course introduces the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. Use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance. Use Python and PowerBI to create and analyze regression, clustering, and classification models.
Note: Knowledge of content and ability to apply skills covered in Courses 1 and 2 of the program is beneficial but not required to take Course 3.
Next Class Date:
Course 3 has been completed for 2024.
Contact us for class dates in 2025.
⊕ Learn more about Course 3
• Course 4: Supply Chain Optimization and Prescriptive Analytics
The course incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. Learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. This serves as a capstone for the program by culminating in a hackathon where you’ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.
Note: Knowledge of content and ability to apply skills covered in Courses 1, 2, and 3 of the program is beneficial but not required to take Course 4.
Next Class Date:
December 9 - 12, 2024
⊕ Learn more about Course 4 or REGISTER
Our Instructors
Melody Shellman
Melody Shellman is a professional education instructor for the Georgia Tech Supply Chain and Logistics institute’s courses within the Supply Chain Analytics Professional certificate program. Melody is an optimization engineer for the consulting division at ORTEC, a top international provider of mathematical optimization software and advanced analytics. The consulting division focuses on building tailor made tools for a client’s unique supply chain. In this role, Melody translates business challenges to mathematics which answer some of the industries toughest questions. As an experienced operations research professional, she has experience with data analytics and optimization across many industries ranging from open-source optimization tools in the energy sector to donor analytics for an environmental advocacy non-profit.
Lorenzo Simons
Lorenzo Simons is a professional education instructor at the Georgia Tech Supply Chain and Logistics Institute, and he serves as an OR engineer in the Center of Excellence at ORTEC. With a commitment to knowledge dissemination and project alignment with contemporary market trends, Lorenzo brings extensive experience to his roles. Prior to his tenure at ORTEC, Lorenzo conducted research at the Universidad Pontificia Comillas in Madrid, Spain. His work has spanned diverse projects, including route planning, supply chain optimization, and electric mobility. Lorenzo's expertise has led him to be sought after as a guest speaker at numerous universities, where he shares insights into how ORTEC utilizes data science and mathematics in practical applications.
Questions?
Read our FAQs or contact ORTEC's Education Team.
