Advanced Demand Planning with R

Advanced Demand Planning with R equips participants with the essential skills and methodologies necessary for effective demand forecasting and inventory management in retail and logistics sectors. This project-based course emphasizes hands-on experience, enabling learners to apply statistical techniques and data analysis using R to optimize demand planning processes. Participants will engage in interactive sessions that foster collaboration and practical problem-solving, culminating in a final project that showcases their ability to implement advanced demand planning strategies.
The course is structured to provide a comprehensive understanding of demand planning concepts, tools, and techniques. By leveraging R, participants will learn to analyze historical data, identify trends, and generate accurate forecasts that drive business decisions. The curriculum is designed to bridge the gap between theoretical knowledge and practical application, ensuring that learners are well-prepared to meet the demands of the job market. Participants will also have the opportunity to publish their project results in Cademix Magazine, enhancing their professional visibility.
Introduction to Demand Planning and Forecasting
Overview of R Programming for Data Analysis
Data Collection and Preparation Techniques
Time Series Analysis and Forecasting Methods
Statistical Modeling for Demand Forecasting
Inventory Management Principles
Demand Planning Software and Tools
Case Studies in Retail and Logistics
Advanced Techniques: Machine Learning in Demand Forecasting
Final Project: Implementing a Demand Planning Solution with R

To develop expertise in demand planning and forecasting using R, enabling participants to make data-driven decisions in a professional context.

Graduates, job seekers, business professionals, and optionally researchers or consultants.

Basic understanding of R programming and statistics.