Courses & Units
GeoData Analytics KEA713
Introduction
Geodata Analytics explains and applies 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. Rigorous approaches to integrating, analysing, visualising and interpreting geochemical, geophysical and geological information are applied to a range of contemporary geoscience problems in mineral exploration, ore extraction and processing, and mining waste management. Geodata analytics is available as an OPTIONAL unit in the Mastery block of the Master of Economic Geology degree and is delivered in three online modules. Module 1 (6 weeks) involves self-directed learning using a mix of prescribed and self-located reading material, short videos and online exercises. Module 2 is a five-day intensive study block involving ~10 hrs lectures and ~30 hours of practicals and tututorials. Module 3 (4 weeks) involves group and individual work on an assignment with targeted online tutorials provided as required.
Summary
| Unit name | GeoData Analytics |
|---|---|
| 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 | |
| Level | Postgraduate |
Availability
| Location | Study period | Attendance options | Available to | ||
|---|---|---|---|---|---|
| Online | Semester 2 | Off-Campus | International | Domestic | |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Note
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Key Dates
| Study Period | Start date | Census date | WW date | End date |
|---|---|---|---|---|
| Semester 2 | 22/7/2024 | 16/8/2024 | 9/9/2024 | 27/10/2024 |
* 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 2024 are indicative and subject to change. Finalised census dates for 2024 will be available from the 1st October 2023. 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
- Construct workflows for semi-automated and repeatable analysis and modelling of geoscience data
- 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 to diverse audiences (e.g. with or 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 |
|---|---|---|---|---|
| 010799 | $2,237.00 | $2,237.00 | not applicable | $5,192.00 |
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
| Teaching Pattern | Delivery of this unit is split into three online modules. Module 1 (6 weeks) involves self-directed learning using a mix of prescribed and self-located reading material, short videos and online exercises. Module 2 is a five-day intensive study block involving ~10 hrs lectures and ~30 hours of practicals and tututorials. Module 3 (4 weeks) involves group and individual work on an assignment with targeted online tutorials provided as required. |
|---|---|
| Assessment | Assessment Task 2: (15%)|Assessment Task 1: Online Quiz (20%)|Assessment Task 3: Image classification assignment (25%)|Assessment Task 4: Geoscience data analysis assignment (40%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
All required readings are listed on the unit MyLO page |
|---|---|
| Recommended | All recommended readings are listed on the unit MyLO page | Links | Booktopia textbook finder |
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.