CSPB 4502 - Data Mining

*Note: This course description is only applicable for the Computer Science Post-Baccalaureate program.听Additionally, students must always refer to course syllabus for the most up to date information.听

  • Credits: 3.0
  • Prerequisites: CSPB or CSCI 2270 Computer Science 2: Data Structures听or CSPB or CSCI 2275 Programming and Data Structures
  • Minimum Passing Grade: C-
  • 罢别虫迟产辞辞办:听Jiawei Han, Micheline Kamber, Jian Pei 鈥淒ata Mining: Concepts and Techniques鈥, 3rd Edition, Morgan Kaufmann, 2011

[video:https://youtu.be/G381T_kSdVo]

Brief Description of Course Content

Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to effectiveness and efficiency. Topics covered include data preprocessing, data warehouse, association, classification, clustering, and mining specific data types such as time-series, social networks, multimedia, and Web data.

Specific Goals for the Course

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  • Apply the concepts and techniques of Data mining on data sets
  • Preprocess and clean data for use in data mining
  • Discover interesting patterns from large amounts of data
  • Data preprocessing听
  • Data warehouse听
  • Association听
  • Classification
  • Clustering
  • Mining specific data types such as time-series, social networks, multimedia, and Web data

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