Postgraduate Certificate in Reverse Logistics Returns Forecasting
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Course details
1 • Introduction to Reverse Logistics: An overview of the field, its applications, and key concepts.
4 • Return Forecasting: A comprehensive introduction to the module, its objectives, and key concepts, including time series analysis, forecasting models, and predictive analytics.
4.3 • Data Analysis for Reverse Logistics: Principles and practices of data analysis, including data visualization, data mining, and statistical techniques, with a focus on problems and issues unique to reverse logistics returns forecasting.
4.4 • Strategic Management for Reverse Logistics: Principles and practices of strategic planning, including scenario analysis, risk assessment, and decision-making techniques, with a focus on applications to reverse logistics returns forecasting.
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3 • Systematic Review and Research in Reverse Logistics: Systematic review of literature, including academic articles, conference proceedings, and industry reports, and research project management.
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4.5 • Independent Project: A practical project, with guidance from a mentor, to apply concepts and skills learned in the other units, including data analysis, strategic management, and forecasting.
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