EECS 837. Data Mining. 3 Hours.

Extracting data from data bases to data warehouses. Preprocessing of data: handling incomplete, uncertain, and vague data sets. Discretization methods. Methodology of learning from examples: rules of generalization, control strategies. Typical learning systems: ID3, AQ, C4.5, and LERS. Validation of knowledge. Visualization of knowledge bases. Data mining under uncertainty, using approaches based on probability theory, fuzzy set theory, and rough set theory. Prerequisite: Graduate standing in CS or CoE or consent of instructor. LEC.

Master of Science in Physics

http://catalog.ku.edu/liberal-arts-sciences/physics-astronomy/ms-physics/

...3 EECS 738 Machine Learning 3 EECS 739 Parallel Scientific Computing 3 EECS 837 Data...

Graduate Certificate in Data Science

http://catalog.ku.edu/engineering/electrical-engineering-computer-science/certificate-data-science/

...of EECS 775: Visualization (3 credits) or DSCI 714: Data Visualization (2 credits) EECS 837...