This paper is a practical introduction to data mining. Students will gain hands-on experience using the WEKA open-source data mining software developed by the Computer Science Department and used by companies and unversities both in New Zealand and overseas.
COMP103 Introduction to Computer Science 1 and
20 points at 200 level in Computer Science.
Official Timetable Information
Witten, Frank, and Hall. (2013) Data Mining: Practical Machine Learning Tools and Techniques. 3rd Ed. Morgan Kaufmann.
Slides will be available on-line at the course website.
You will have access Windows machines in Lab 5, R-block, throughout the course.
Lab work (tutorials) : 30%
Test : 15%
Exam : 35%
Internal assessment/final examination ratio 2:1
All assessment is compulsory. An overall mark of 50% is required for a pass, with a minimum of 40% in the final exam and a minimum of 40% for coursework.
Class attendance is expected. You are responsible for all material covered in class.
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