HADM 3275: Introduction to Machine Learning in Business

Spring. 3 credits. Student option grading.

Prerequisite: HADM 2011 or other introductory statistics course or instructor permission. Priority given to: Nolan Students. Course can qualify for Hospitality Analytics Specialization elective. Co-meets with HADM 5275.

Instructors

• Jingwei Zhang (jz2293) - Spring 2025

Description

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.