The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.
Prerequisites: CSE 5709; Open to graduate students in the M.S. in Data Science program. Recommended preparation: Python programming including open-source libraries: scikit-learn, Numpy, Matplotlib, introductory statistics
Grading Basis: Graded
This course presents an introduction to data mining algorithms in the areas of classification, association analysis, clustering, and anomaly detection, with an emphasis on a conceptual understanding these algorithms along with their application in real-world problems and domains.
No classes found.