Machine Learning in Retail Environments delves into the transformative impact of machine learning technologies tailored for the retail sector. This course equips participants with hands-on experience in applying machine learning algorithms to optimize various retail processes, from inventory management to customer experience enhancement. By engaging in project-based learning, attendees will gain practical insights into real-world applications and develop skills that are immediately applicable in the workforce.
Participants will explore a range of topics, including predictive analytics, recommendation systems, and sales forecasting. The course culminates in a final project where learners will implement a machine learning solution addressing a specific challenge within a retail context. This project not only solidifies their understanding but also provides an opportunity for publication in Cademix Magazine, showcasing their work to a wider audience.
Introduction to Machine Learning Concepts in Retail
Data Collection and Preprocessing Techniques
Predictive Analytics for Sales Forecasting
Customer Segmentation using Clustering Algorithms
Recommendation Systems and Personalization Strategies
Inventory Optimization with Machine Learning Models
Anomaly Detection in Retail Transactions
Natural Language Processing for Customer Feedback Analysis
Implementing Machine Learning Solutions in Retail Software
Final Project: Developing a Machine Learning Application for a Retail Problem