Machine Learning and Artificial Intelligence in Business Analytics

Catalog description

Advances in computational analytics including Machine, Deep and Statistical Learning (ML) provide powerful methods for developing mathematical "learning" models that can autonomously parse, learn from, and make predictions from data to improve performance with "experience". In deep learning, large neural networks are leveraged to achieve artificial intelligence (AI), enabling machines to mimic human behavior. This course covers principles, algorithms, and applications of machine learning from a business analytics perspective. Specifically, the course will provide a practical understanding of modern machine learning techniques including regression and classification methods, resampling methods and model selection, regularization, perceptron and artificial neural networks, tree-based methods, support vector machines and kernel methods, and grouping methods. Prereq or Coreq: BUAI/MSBA 434 or BUAI/MSBA 444. Prereq: Master of Business Analytics & Intelligence students only and (BUAI/MSBA 492 or SCMG/MSOR 492 or BTEC 420 ).