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 | Sciences and Engineering School of Natural Sciences |
| Discipline | CODES ARC |
| Coordinator | Doctor Matthew Cracknell |
| Delivered By | |
| Level | Postgraduate |
Availability
Specific information on 2027 unit availability will be available in August
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
2027 fee information will be available in August.
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 |
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.