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Research School of Earth Sciences · ANU College of Science and Medicine
This course is for Honours students 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 include: hypothesis testing, regression, cluster analysis, dimension reduction techniques, error propagation, Monte Carlohods and solving problems with random numbers, bootstrapping, fitting parameters and probabilistic inference.
Homework Data set Processing Assignment 1, includes a presentation
Learning outcomes 1, 2, 3, 4, 5
Homework Data set Processing Assignment 2, includes a presentation
Learning outcomes 1, 2, 3, 4, 5
The expected workload will consist of approximately 130 hours throughout the semester including: - Face-to-face component which consists of 4 x 3-hour seminars/workshops for six weeks. - Approximately 58 hours of self-directed study which will include preparation for the seminars, presentations, and other assessment tasks.
A reading list will be provided during the course.