• Offered by Research School of Earth Sciences
  • ANU College ANU Joint Colleges of Science
  • Classification Advanced
  • Course subject Earth and Marine Science
  • Areas of interest Earth and Marine Sciences, Algorithms and Data, Earth Physics, Geology, Environmental Science
  • Academic career PGRD
  • Course convener
    • Prof Malcolm Sambridge
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Second Semester 2020
    See Future Offerings
  • STEM Course

This course includes an on campus activity/ies. Check timetable for details. Contact course convener if you are unable to travel to Canberra.

Data science is the most powerful tool we have for separating scientific fact from fiction. The aim of this course is to provide an advanced background in statistical and computational techniques that are useful in the analysis and characterisation of Earth Science data. A focus will be placed on conceptual understanding of how specific data science techniques work and the situations in which they can and cannot be applied. The course will focus on practical examples, providing the opportunity for hands-on learning through the processing of data sets with Python. Specific topics to be discussed in lectures will be; Monte Carlo methods and solving problems with random numbers, bootstrapping, fitting parameters and probabilistic inference. Students will complete an individually-designed assignment tailored to their specific interests. The experience gained in this course will help students approach their own research.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Understand and explain the theoretical and practical aspects of a suite of statistical techniques employed commonly in quantitative Earth Science research.
  2. Evaluate Earth Science data sets in a critical manner using appropriate analysis techniques.
  3. Assess the quality of data needed to obtain specific goals.
  4. Critique the advantages, disadvantages and applicability of data science techniques to a range of problems in the Earth Sciences.
  5. Communicate effectively the foundations of specific data science tools to Earth Science research problems.

Indicative Assessment

  1. A written report detailing their project work, solution to given problems and ideas for how their work can be extended in the future. This report should evaluate the data science techniques on which their project focused and provide critical insights into the capabilities and shortcomings of different approaches (70) [LO 1,2,3,4]
  2. 15 minute oral presentation to communicate to their peers the problem addressed in their project and their solutions to the tasks they were set. Students will be expected to answer questions about their project and provide a clear justification for choices they made in selecting and applying given techniques to their problem (30) [LO 4,5]

In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle. 

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

35 hours of lectures accompanied by 30 hours of workshops focusing on individual projects. Students will be required to complete approx. 65 hours of self-study, based on a combination of class assignments and individual project work.

Inherent Requirements

Not yet determined

Requisite and Incompatibility

To enrol in this course you must be enrolled in the Master of Earth Sciences (Adv) or the Master of Science in Earth Sciences and have completed EMSC8033 Computational Geosciences. Incompatible with EMSC4123.

Prescribed Texts

A reading list will be provided during the course. Specific reading lists will be developed for individual students based on their tailored projects.

Assumed Knowledge

Basic knowledge of Mathematics

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2020 $4050
International fee paying students
Year Fee
2020 $5760
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
8766 27 Jul 2020 03 Aug 2020 31 Aug 2020 30 Oct 2020 In Person View

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