Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
On Comparing Classifiers: Pitfalls toAvoid and a Recommended Approach
Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Methods for evaluating and creating data quality
Information Systems - Special issue: Data quality in cooperative information systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A data mining course for computer science: primary sources and implementations
Proceedings of the 37th SIGCSE technical symposium on Computer science education
A data mining course for computer science and non-computer science students
Journal of Computing Sciences in Colleges
Names: a new frontier in text mining
ISI'03 Proceedings of the 1st NSF/NIJ conference on Intelligence and security informatics
Lessons learned in the design of an undergraduate data mining course
Journal of Computing Sciences in Colleges
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Data mining courses are increasingly being taught at many universities at both undergraduate and graduate levels. This paper reports on a new graduate level data mining course run for the first time in 2007 at a major Australian university. The course had almost 20% enrolments of industry based participants from both private and public sector organisations. This paper discusses the student population and presents the course structure and assessment. An empirical evaluation of student responses, conducted at the end of the course, is then provided, with an emphasis on differences in responses from graduate students and external participants. To the best of the author's knowledge, this is the first such detailed empirical evaluation of a data mining course.