Introduction To Supply Chain Analytics

Supply Chain Analytics, Supply Chain Management, Data Analytics Business Analytics,Logistics Operations,Management Data

What you'll learn
Understand the Fundamentals of Supply Chain Analytics
Develop Core Analytical Skills
Analyze Key Supply Chain Processes
Apply Supply Chain Analytics in Real-World Scenarios

Requirements
No Prerequisites needed

Description
Course Description:This course provides an introduction to the concepts and techniques of supply chain analytics. Students will learn how to leverage data and analytical methods to improve the efficiency, resilience, and profitability of supply chains. The course will cover a range of topics, including data collection and preparation, descriptive and predictive analytics, supply chain performance measurement, and the application of analytics to key supply chain processes such as demand forecasting, inventory management, and logistics.Learning Outcomes:Upon successful completion of this course, you will be able to:Understand the key concepts and principles of supply chain analytics.Apply data analysis techniques to solve real-world supply chain challenges.Interpret and communicate analytical findings effectively to stakeholders.Develop data-driven solutions to improve supply chain efficiency and performance.Gain a competitive edge in the evolving field of supply chain management.Who Should Take This Course:This course is ideal for:Students pursuing degrees in All engineering studies including but not limited to Supply Chain Management, Logistics, Operations Management, Business Analytics, and related fields.Professionals seeking to advance their careers in supply chain management, Business analytics, Supply chain analytics, Data analyst, and logistics.Individuals interested in developing a strong foundation in data-driven decision-making within the supply chain context.

This course is designed for undergraduate and graduate students, working professionals in supply chain roles, and individuals seeking to enter the field who possess a foundational understanding of quantitative concepts and a strong interest in data-driven decision-making.