EAE5069 · Data analysis in earth sciences

Overview

This unit will provide you with the skills needed for advanced data analysis in Earth Sciences using Python. You will learn techniques for managing, analysing and communicating complex data based on real-world scenarios or your own research. The analysis component will include standard methods such as correlations, power spectra, regridding and curve-fitting.

Areas of study: Master of Science

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Apply advanced programming to manage and manipulate data in Python;
2. Apply major techniques of data analysis in Earth Science;
3. Communicate data-analysis results at the level of peer-reviewed research papers;
4. Publish reproducible methodology using best practice for open-source data analysis;
5. Be able to independently asses and troubleshoot data analysis coding problems.

Workload

This unit is taught in an intensive manner over 6 weeks as follows: • 20 hours of interactive workshops (Weeks 1 and 2); • One 5-hour workshop (Weeks 3 and 4) and • 94 hours of independent study over 6 weeks, which will include guided activities and preparation of a major assessment

Student experience, not official rules. Nothing here changes what the Handbook says.