Courses

CMSC 635: Knowledge Discovery and Data Mining

Covers knowledge discovery and data mining concepts, tools and methods; provides hands-on experience based on a project involving analysis of large real-life data. Topics include the knowledge discovery process, data storage and representation, preprocessing algorithms for missing data imputation, feature selection and discretization; unsupervised learning algorithms for clustering and association mining; supervised learning algorithms including decision trees, Bayesian models and introduction to support vector machines and neural networks; ensemble learning; protocols and measures for validation of predictive models; and data security and privacy issues.

Total Credit Hours: 3
Semester(s):
Spring 2018
Prerequisites:
CMSC 401 or corequisite: CMSC 501. Enrollment restricted to students with graduate standing in computer science
Instructor:
Dr. Lukasz Kurgan
Instructor Email:
lkurgan@vcu.edu

Weekly Live Sessions

Mon Tue Wed Thu Fri Sat

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Questions? Contact the VCU CGEP Director:

Dr. Gregory Triplett   •   Ph: (804) 828-5387   •   getriplett@vcu.edu