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. (2011) 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 2 (RG.07), 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.
Follow this link for Academic Integrity information and this link for detailed explanation of How to prevent plagiarism in Computer Science assessment items.
Follow this link for information on Performance Impairment.
Student Concerns and Complaints
Follow this link for Student Concerns and Complaints information.
Application for Extension
Follow this link for information on applying for an Extension.
Review of Grade
Follow this link for information on applying for a Review of Grade.
Your attention is drawn to the following regulations and policies, which are published in the University Calendar: