Courses & Units
GeoData Analytics KEA713
Introduction
The GeoData Analytics course will be to provide industry-based geoscientists with an understanding of the fundamental concepts of database handling and manipulation, statistical analyses, pattern recognition and machine learning for the processing, analysis and modelling of large volumes of multivariate geoscience data. This course will focus on rigorous approaches of the above methods for extracting and visualising meaningful information from geochemical, geophysical and geological information with applications for mineral exploration; ore extraction and processing; and waste management. The unit volume of learning consists of 150 hours of assessment, accompanied by 75 hours of taught content, either online and/or in person.
Summary
Unit name | GeoData Analytics |
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Unit code | KEA713 |
Credit points | 25 |
College/School | College of Sciences and Engineering School of Natural Sciences |
Discipline | CODES ARC |
Coordinator | Doctor Matthew Cracknell |
Delivered By | University of Tasmania |
Level | Postgraduate |
Availability
Location | Study period | Attendance options | Available to | ||
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Hobart | Semester 2 | Off-Campus | International | Domestic |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Key Dates
Study Period | Start date | Census date | WW date | End date |
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Semester 2 | 11/7/2022 | 9/8/2022 | 29/8/2022 | 16/10/2022 |
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2022 are indicative and subject to change. Finalised census dates for 2022 will be available from the 1st October 2021. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Describe methods for the preparation and processing of geoscience data for multivariate analysis.
- Develop workflows for semi-automated and repeatable analysis and modelling.
- Explain how pattern recognition and machine learning can be used for computer-assisted interpretation and inference in the minerals industry.
- Analyse geoscience data to identify previously unrecognised relationships and/or patterns to address mineral industry problems.
- Communicate data analytics results and models using a variety of media to an audience with and without geoscience domain expertise.
Fee Information
Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
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010799 | $2,005.00 | $2,005.00 | not applicable | $4,708.00 |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Teaching
Assessment | Test or quiz (20%)|Assignment (25%)|Assignment (40%)|Discussion Posts (online) (15%) |
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Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
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The University reserves the right to amend or remove courses and unit availabilities, as appropriate.