Practical Data Mining - COMP321 (2017)

This paper is a practical introduction to data mining. It covers important aspects of the data mining process such as feature selection, model building, parameter tuning and final evaluation.

Paper Information

Points: 20.0
Prerequisite(s): (COMP103 or ENGG182) and 20 points at 200 level in Computer Science
Internal assessment / examination: 2:1

Semesters and Locations

Occurrence Code When taught Where taught
17B (HAM)B Semester : Jul 10 - Oct 29, 2017 Hamilton
17B (TGA)B Semester : Jul 10 - Oct 29, 2017 Tauranga

Timetabled Lectures for Practical Data Mining (COMP321)

COMP321-17B (HAM)
Mon5:00 PM6:00 PMS.G.02Jul 10 - Oct 8
Wed12:00 PM1:00 PMS.G.02Jul 10 - Oct 8
COMP321-17B (TGA)
Mon5:00 PM6:00 PMBOPP.DT.403Jul 10 - Oct 8
Wed12:00 PM1:00 PMBOPP.DT.403Jul 10 - Oct 8

NB:There may be other timetabled events for this paper such as tutorials or workshops.
Visit the online timetable for COMP321 for more details

Indicative Fees for Practical Data Mining (COMP321)

Occurrence Domestic International
 Tuition Resource 
17B (HAM) $1131 $0 $4663
17B (TGA) $1131 $0 $4663
You will be sent an enrolment agreement which will confirm your fees.
Tuition fees shown below are indicative only and may change. There are additional fees and charges related to enrolment - please see the Table of Fees and Charges for more information.

Paper Outlines for Practical Data Mining (COMP321)

The following paper outlines are available for Practical Data Mining (COMP321).
If your paper occurrence is not listed contact the Faculty or School office.

Additional Information

Available Subjects:  Computer Science | Applied Computing | Statistics

Other available years: Practical Data Mining - COMP321 (2018)

Paper details current as of : 19 January 2018 11:30am
Indicative fees current as of : 20 January 2018 4:30am

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