Course Websites
IE 529 - Stats of Big Data & Clustering
Last offered Spring 2026
Official Description
Covers 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: Prerequisite: MATH 416 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.
Related Faculty
Documents
| Title | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
|---|---|---|---|---|---|---|---|---|
| Stats of Big Data & Clustering | A | 68102 | ONL | 4 | - | Carolyn L Beck | ||
| Stats of Big Data & Clustering | B | 75698 | LCD | 4 | 1500 - 1620 | T R | 3100 Sidney Lu Mech Engr Bldg | Carolyn L Beck |