CS 2756 - PRINCIPLES OF DATA MINING

Minimum Credits: 3
Maximum Credits: 3
Data mining is the process of efficient supervised or unsupervised discovery of non-trivial and useful knowledge and patterns from collections of data. This proposed course aims to provide a discussion of multiple common tasks in data mining, including association rules/sequential patterns, classification, anomaly detection, avoiding false discoveries, and clustering. Besides, this course will also introduce the latest advances in data mining and provide extensive hands-on experience via programming projects. Non-CS students interested in enrolling must suggest project ideas and obtain the instructors written permission to override the enrollment requirements.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PREQ: CS 1656

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