AEM 5275

AEM 5275

Course information provided by the Courses of Study 2024-2025.

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.

When Offered Spring.

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

Syllabi:
  •   Regular Academic Session.  Combined with: AEM 3275

  • 3 Credits Opt NoAud

  • 19991 AEM 5275   LEC 001

    • TR
    • Jan 21 - May 6, 2025
    • Zhang, J

  • Instruction Mode: In Person

Syllabi:
  •   Regular Academic Session.  Combined with: AEM 3275

  • 3 Credits Opt NoAud

  • 19992 AEM 5275   LEC 002

    • TR
    • Jan 21 - May 6, 2025
    • Zhang, J

  • Instruction Mode: In Person