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SIGCSE
2006
ACM

A data mining course for computer science: primary sources and implementations

10 years 10 months ago
A data mining course for computer science: primary sources and implementations
An undergraduate elective course in data mining provides a strong opportunity for students to learn research skills, practice data structures, and enhance their understanding of algorithms. I have developed a data mining course built around the idea of using research-level papers as the primary reading material for the course, and implementing data mining algorithms for the assignments. Such a course is accessible to students with no prerequisites beyond the traditional data structures course, and allows students to experience both applied and theoretical work in a discipline that straddles multiple areas of computer science. This paper provides detailed descriptions of the readings and assignments that one could use to build a similar course. Categories and Subject Descriptors I.2.6 [Artificial Intelligence]: Learning—concept learning, induction; I.5.2 [Pattern Recognition]: Design Methodology—classifier design and evaluation; I.5.3 [Pattern Recognition]: Clustering—algorithm...
David R. Musicant
Added 14 Jun 2010
Updated 14 Jun 2010
Type Conference
Year 2006
Where SIGCSE
Authors David R. Musicant
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