Note: This is an archived Handbook entry from 2011.
|Dates & Locations:|| |
This subject is not offered in 2011.
|Time Commitment:||Contact Hours: 2 x one hour lectures per week, 1 x 1 hour workshop per week |
Total Time Commitment: Estimated total time commitment of 120 hours.
Study Period Commencement:
Not offered in 2011
|Recommended Background Knowledge:||None|
|Non Allowed Subjects:||None|
|Core Participation Requirements:||For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements of this entry.The University is dedicated to provide support to those with special requirements. Further details on the Disability support scheme can be found at the Disability Liaison Unit Website:http://www.services.unimelb.edu.au/disability|
Associate Professor James Bailey
This subject introduces students to advanced data analysis and information management techniques. It includes areas such as automated knowledge discovery (finding relationships and patterns in large and complex data sets), data mining techniques such as clustering, classification, regression and association rules; data mining platforms; spreadsheets as modelling and analysis tools; and decision making technologies and systems.
On completion of this subject students should be able to:
Two projects, one mid-semester (20%) and one end-of -semester (20%), expected to take about 20 hours each and require a report of about 1000 words each; and a 2-hour end-of-semester written examination (60%).
Ian H. Witten and Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques, 2nd Ed, ISBN 0-12-088407-0
|Breadth Options:|| |
This subject potentially can be taken as a breadth subject component for the following courses:
You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.
|Fees Information:||Subject EFTSL, Level, Discipline & Census Date|
On completion of this subject students should have developed the following generic skills:
This subject is available for science credit to students enrolled in the BSc (new degree).
Please note: As this subject will not be offered in 2011. Students who have an appropriate background may enrol in COMP90049, Knowledge Technologies.
Bachelor of Science |
Diploma in Informatics
Science Informatics |
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