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Unit of study_
OLET1618: Data Science in Astronomy: Algorithms
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 investigate the challenges of working with large datasets. How to implement algorithms that work and how to think about scaling to large datasets. The focus is on practical skills - all the activities will be done in Python 3, a 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.
| Code | OLET1618 |
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| Academic unit | Physics Academic Operations |
| Credit points | 2 |
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Prerequisites:
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None |
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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. |
At the completion of this unit, you should be able to:
- LO1. demonstrate an understanding of some astronomical phenomena
- LO2. understand the type of problems that may arise when dealing with big data
- LO3. discuss ways you can improve computational solutions to data analysis problems
- LO4. write short programs (in Python) to analysis datasets.
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