Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits. To analyse this data scientists need to be able to think computationally to solve problems. In this course you will learn how to manage your data with databases, and use the SQL language to ask questions about your data. You will also learn how to explore your data with machine learning tools. The focus is on practical skills - all the activities will be done in Python 3, and modern programming language used throughout astronomy. This will be run as a 0 cp + 2 cp unit of study. Students should have strong programming skills in Python 3, with a good understanding of loops, decisions and user-defined functions.
Unit details and rules
Academic unit | Physics Academic Operations |
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Credit points | 2 |
Prerequisites
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None |
Corequisites
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None |
Prohibitions
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None |
Assumed knowledge
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Students should have strong programming skills in Python 3, with a good understanding of loops, decisions and user-defined functions. |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Jesse Van de Sande, jesse.vandesande@sydney.edu.au |
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