Geodata Analytics: Fundamentals

Learn the fundamental skills of data analytics, such as data management, data preparation and image analysis and segmentation. Register now and start anytime.

Time:Price
$990.00
Time:Duration
42 hours
Time:Delivery
Online
Time:Starts
8 Aug - 18 Sept

About this course

Geodata Analytics: Fundamentals will provide you will the essential knowledge and skills to get started in the Geodata Analytics series.

This fully online, self-paced course will cover a range of industry-relevant topics including: understanding basic statistics, databases and exploratory data analysis, classification and querying of database queries, and image analysis and segmentation.

You will also learn about data formats and data preparation such as filtering and transformation, and learn from peer-review literature and a case study involving data analytics.

Successful completion of all assessments in this course series will make you eligible to receive credit into the Master of Economic Geology. For more information please contact short.course@utas.edu.au.

Who should do this course?

This course is designed for mineral industry professionals and under-employed industry professionals looking to increase their skills and knowledge.

All participants must complete this course before registering for the next courses in this series; Geodata Analytics: Methods and Tools and Geodata Analytics: Collaboration, Interpretation and Communication.

Course Structure

This course is fully online and self-paced, allowing you to study when it’s convenient for you. As a general guide, we recommend allocating 42 hours to complete this course. Learning materials includes video content, online quizzes, short answers questions and online discussion boards. You will have access to all course materials until January 2023.

All participants will receive a Certificate of Completion after completing this course.

What you will learn

Identify appropriate methods for analysing geoscience data based on the nature of input data set and desired outcome/s.

Define the structure workflows for reproducible analysis of geoscience data.

Explain how computer-assisted interpretation can aid analysis of different geoscience data sets.

Evaluate the suitability of different data analysis approaches to a given data set to achieve a desired outcome.

Meet your instructors

Dr Matthew Cracknell

Dr Matthew Cracknell is a Postdoctoral Research Fellow in Earth Informatics at the ARC Industrial Transformation Research Hub for Transforming the Mining Value Chain (TMVC). He also lectures 2nd and 3rd year geophysics students for the School of Natural Sciences (Earth Sciences) and conducts research at the Centre for Ore Deposit and Earth Sciences (CODES). His research focuses on the use of data mining and pattern recognition techniques for integrating and analysing geoscience data.

View Matthew's Staff Profile