• Offered by Fenner School of Environment and Society and the Research School of Earth Sciences
  • ANU College ANU College of Science and Medicine / ANU College of Systems and Society
  • Course subject Earth and Marine Science
  • Areas of interest Earth and Marine Sciences, Resource Management and Environmental Science, Statistics, Computer Science, Algorithms and Data
  • Academic career UGRD
  • Course convener
    • AsPr David Heslop
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in First Semester 2027
    See Future Offerings
  • STEM Course

Discover how to ask better questions — and find meaningful answers. 

Data science is the most powerful tool we have for separating scientific fact from fiction. In this course, you'll explore practical and relevant problems in Earth and Environmental Sciences by learning how to interpret data, assess uncertainty, model outcomes and make informed decisions. You'll tackle questions like: 

“How can I make predictions of the future?”  

"Where should I expend the most effort to improve my results?”  

“What accuracy and how many measurements do I need?”  

“Is this result meaningful, or just random chance?” 

"Why is this happening and what's driving the change?"


Using real-world examples and hands-on activities, you’ll develop analytical thinking and quantitative problem-solving skills that are highly valued across science and industry. This course provides a foundation in essential tools, including data analysis, modelling and statistics, through engaging, problem-based learning tailored to the challenges Earth and Environmental scientists face today. 

Learning Outcomes

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

  1. Assess suitability and quality of data sets required for a range of Earth and Environmental science problems;
  2. Develop sound data management skills using contemporary best practice (e.g. FAIR data);
  3. Reflect on Earth and Environmental Science research according to the quality of research methods, appropriateness of analyses and conclusions;
  4. Independently apply the concepts of statistics, mathematics and programming to Earth and Environmental problems;
  5. Write code in Python/R to analyse, visualise and model data and create simple simulations;
  6. Apply a range of strategies to manage and successfully produce effective code in a collaborative environment;
  7. Develop self as a life-long learner and communicate data driven concepts effectively.

Indicative Assessment

  1. Collaborate on a programming task using GitHub to develop a data analysis workflow (15) [LO 2,5,6,7]
  2. Individual Project report write up / presentation / showcase (40) [LO 1,3,4,5,7]
  3. Individual Project plan including data plan, tooling plan, time-frames (25) [LO 1,4,7]
  4. Team lab-notebooks for project activities (5) [LO 1,3,6,7]
  5. Quizzes in weeks 2,3,4 (hurdle / mastery) (15) [LO 2,4,5,6]

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

The expected workload will consist of approximately 130 hours throughout the semester including:

Face-to face component which is expected to consist of:

  • Weeks 1-4: 2 x 2 hour practicals 1 x 1 hour tutorial
  • Weeks 5-6 and 7-12: 2 hour Lectorial + 3 hour practical
  • 1/2 day student conference (presentations or posters)
  • Approximately 60-70 hours of self-directed study which will include preparation for lectures, practicals and other assessment tasks.


Inherent Requirements

No specific inherent requirements have been identified for this course.

Requisite and Incompatibility

To enrol in this course, students must have completed 24 units of prior tertiary study.

Prescribed Texts

A list of prescribed texts will be provided within the class summary.

Fees

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

Commonwealth Support (CSP) Students
If you 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). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found 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
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.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
5288 22 Feb 2027 01 Mar 2027 31 Mar 2027 28 May 2027 In Person N/A

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions