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...

• Type: Conference
• Year: 2006
• Where: SIGCSE
• Authors: David R. Musicant
• Keywords: Data Mining, Data Mining Course, Data Structures, Education, SIGCSE 2006