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.
Data-driven AstronomyThe University of Sydney
About this Course
Skills you will gain
- Python Programming
- Machine Learning
- Applied Machine Learning
Syllabus - What you will learn from this course
Thinking about data
Big data makes things slow
Querying your data
Managing your data
- 5 stars85.27%
- 4 stars12.97%
- 3 stars1.27%
- 2 stars0.23%
- 1 star0.23%
TOP REVIEWS FROM DATA-DRIVEN ASTRONOMY
This course is exceptionally good, well developed and structured. The content of the course is good. The teachers have demonstrated the concept well. I would like to learn more on this concept.
Great and quick way to learn things. Thanks for the troubles taken to put this together. Some of the computational exercises could do with a little more clarity of language. But, overall, Great!
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.
Such a wonderful course. It had a very good mix of astronomy and computer science. The programming activities were especially good and the lectures were very informative. I highly recommend.
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