Who should attend
This course is designed for experienced business professionals who perform (or want to perform) data analyses of any form in the area of supply chain, and who seek to get more from their supply chain data. This course will benefit learners who want additional tools and who want to become a change agent that tackles strategic supply chain goals.
About the course
As the third course in the Supply Chain Analytics Professional program, you’ll be introduced to 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. You’ll learn to forecast future demand and use this information to evaluate inventory policies, while also learning the importance of and how to perform customer segmentation. The course will cover regression (trees), advanced time series forecasting, various clustering techniques (such as k-means), decision trees, random forests, neural nets, logistic regression, and Bayes classifiers. Using Power BI and Python, you’ll apply the techniques to sensor data of the fictional Cardboard Company’s paper production to build an anomaly detection model that supports proactive production maintenance planning.
What You Will Learn
- Machine learning (ML) techniques
- ML algorithms
- How to apply ML in demand forecasting, sales and operation planning (S&OP), and inventory management
- ML in production planning and predictive maintenance
- Advanced analytics techniques using engine downtime predictive modeling example
- Supply chain professionals collaborating in warehouse
How You Will Benefit
- Understand the use of regression and clustering techniques in supply chain planning.
- Apply ML in demand forecasting, S&OP, and inventory management.
- Use Python and Power BI to build forecasting models.
- Apply advanced analytics techniques to build planning tools that can leverage large and real-time data sets.
- Understand and apply ML techniques specific to production planning and predictive maintenance.
- Leverage the Microsoft Azure platform for collaborative planning, visualization, and data management.
- Build an anomaly detection model that supports production maintenance planning.
Mr. Brown has over 30 years of experience in supply chain management operations and services as an operations manager, consultant, educator, and executive recruiter. Tim was appointed as Managing Director in the Georgia Tech Supply Chain & Logistics Institute (SCL). SCL is a unit of Georgia ...
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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.