HADM 3275

Introduction to Machine Learning in Business

Course Description

Course information provided by the 2025-2026 Catalog.

This course aims to provide business majors with essential machine learning concepts and practical skills. Through a blend of theory and hands-on experiences, you'll learn how to utilize data-driven insights in the business world. The focus is on analyzing data effectively, improving prediction performance, and extracting valuable information for managerial decision-making. We'll apply machine learning to diverse business contexts, including predicting customer behavior, forecasting prices, and natural language processing. Each application involves specific machine learning tasks like classification, numeric prediction, and clustering. We'll tackle these tasks using various models, such as logistic regressions, support vector machines, decision-trees, ensemble learning (e.g., random forests and boosting), and neural networks. Throughout the course, we'll emphasize hands-on implementation using Python-based machine learning packages like scikit-learn, and make the advanced machine learning tools (e.g., XGBoost) accessible to business students.

Prerequisites HADM 2011 or other introductory statistics course or instructor permission.

Enrollment Priority Priority given to: Nolan Students.

Last 4 Terms Offered 2025SP

Outcomes

• Identify opportunities and challenges associated with machine learning in various business contexts.
• Implement different machine learning models and evaluate the model performance.
• Interpret and visualize analytical conclusions and insights.
• Design machine learning based solution to business context problems.

View Enrollment Information