HADM 5275
Last Updated
- Schedule of Classes - January 5, 2026 3:59PM EST
Classes
HADM 5275
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.
Enrollment Priority Priority given to: Nolan Students.
Last 1 Terms Offered 2025SP
Regular Academic Session. Combined with: HADM 3275
-
Credits and Grading Basis
3 Credits Opt NoAud(Letter or S/U grades (no audit))
-
Class Number & Section Details
-
Meeting Pattern
- TR Statler Hall 198
- Jan 20 - May 5, 2026
Instructors
Zhang, J
-
Additional Information
Instruction Mode: In Person
Share
Disabled for this roster.
