Detailed Course Information

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CSC 305 - Data Mining and Applications
Data Mining and Applications Prerequisite: CSC 210 Data mining is the process of extraction of implicit, previously unknown and potentially useful information from data. This course provides fundamentals of data mining and knowledge discovery including: knowledge representation, association analysis, clustering, predictive modeling, anomaly detection, visualization and so on. The emphasis will be laid on using techniques in different settings, including business, medicine, science and engineering, rather than developing new techniques or algorithms. 3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Computer Science Department Course Attributes: NewMedia Computation Conc Prerequisites: Prerequisite CSC 305 General Requirements: Course or Test: CSC 210 May not be taken concurrently.

CSC 305 - Data Mining and Applications

Data Mining and Applications
Prerequisite: CSC 210

Data mining is the process of extraction of implicit, previously unknown and potentially useful information from data. This course provides fundamentals of data mining and knowledge discovery including: knowledge representation, association analysis, clustering, predictive modeling, anomaly detection, visualization and so on. The emphasis will be laid on using techniques in different settings, including business, medicine, science and engineering, rather than developing new techniques or algorithms.

3.000 Credit hours
3.000 Lecture hours

Levels: Undergraduate
Schedule Types: Lecture

Computer Science Department

Course Attributes:
NewMedia Computation Conc

Prerequisites:
Prerequisite CSC 305

General Requirements:
Course or Test: CSC 210
May not be taken concurrently.

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Detailed Course Information		Current Aug 17, 2019