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; how to use databases to manage your data; and how to learn from your data with machine learning tools. The focus is on practical skills - all the activities will be done in Python 3, a modern programming language used throughout astronomy.
Our excellence in research and teaching makes the University of Sydney one of the top universities in Australia and highly ranked among the best universities in the world. In 2020, we were ranked second in the Times Higher Education (THE) University Impact Rankings, and first in Australia in the QS Graduate Employability Rankings.
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Very Nice course, materials well explained though the programming exercises were very difficult for me, as I did not had that much in depth knowledge of python, for which I had to take additional help
Really amazing course! Gave me insights into how data analysis works in the field of astronomy and how one can use different machine learning techniques to classify the huge amounts of data generated.
Its been amazing to learn about the celestial objects, stars, galaxies. The lectures and quizzes spurred in me to explore new material online. Great hands on exercises in python and machine learning
This is a great course for anyone wanting to do data science with astronomical datasets. The lectures are clear and interesting and the activities are well structured. I really enjoyed this course!
Is financial aid available?
What programming background is assumed?
We assume you are familiar with basic programming in a modern programming language including variables, control structures, data structures, functions, and working with files. In this course we will use Python 3.
We'll walk through all the examples and provide lots of support, so jump in and have a go. If haven't done any programming for a while, you might want to brush up before you start.