This course delves into the sophisticated methodologies of AI forecasting specifically tailored for the retail sector. Participants will engage in hands-on projects that allow them to apply theoretical concepts to real-world scenarios, enhancing their understanding of predictive analytics. The curriculum is designed to equip learners with the skills necessary to leverage AI tools for accurate demand forecasting, inventory management, and sales predictions, ultimately driving business growth and operational efficiency.
Through interactive learning experiences, participants will collaborate on projects that culminate in the publication of their findings in Cademix Magazine. This not only showcases their expertise but also contributes to the broader discourse on AI applications in retail. The course emphasizes practical skills, ensuring that graduates leave with a robust portfolio of work that demonstrates their capabilities in AI forecasting techniques.
Introduction to AI and Machine Learning in Retail
Data Collection and Preprocessing for Forecasting
Time Series Analysis and Forecasting Models
Advanced Regression Techniques for Retail Predictions
Neural Networks and Deep Learning Applications
Seasonal Decomposition of Time Series Data
Demand Forecasting Techniques and Tools
Inventory Optimization Strategies using AI
Sales Forecasting and Revenue Management
Final Project: Developing an AI Forecasting Model for a Retail Scenario