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Subject offerings of new and developing areas of knowledge in industrial engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: 1 to 4 undergraduate hours. 1 to 4 graduate hours. May be repeated in the same or separate terms if topics vary to a maximum of 9 hours.

Machine Learning includes the design and the study of algorithms that can learn from experience, improve their performance, and make predictions. Students will learn the concepts behind different supervised machine learning algorithms (KNN, decision trees, logistic and linear regression, SVM, random forest, and gradient boosting) and implement them in Python using packages; pandas, NumPy and scikit-learn. All the data for this course features unique real-world financial datasets. Priority given to incoming MS Financial Engineering Program students.