IE 529 - Stats of Big Data & Clustering
|Stats of Big Data & Clustering||IE529||A||66823||LCD||1300 - 1350||M W F||403B2 Engineering Hall||Carolyn L Beck|
|Stats of Big Data & Clustering||IE529||ONL||69486||ONL||-||Carolyn L Beck|
This course will cover various foundational topics in data science. Parametric and non-parametric methods. Hypothesis testing; Regression; Classification; Dimension reduction; and Regularization. Unsupervised and semi-supervised learning, along with a few case studies. Course Information: 4 graduate hours. No professional credit. Prerequisite: MATH 415 and IE 300 or equivalent. All ISE graduate students and students enrolled in the Master of Science in Advanced Analytics (MSAA) are eligible to take the course.