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.
Offered By
Data-driven Astronomy
The University of SydneyAbout this Course
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- Python Programming
- Machine Learning
- Applied Machine Learning
- SQL
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Syllabus - What you will learn from this course
Thinking about data
Big data makes things slow
Querying your data
Managing your data
Reviews
- 5 stars85.29%
- 4 stars12.95%
- 3 stars1.27%
- 2 stars0.23%
- 1 star0.23%
TOP REVIEWS FROM DATA-DRIVEN ASTRONOMY
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.
very comprehensive course, a little bit advance but in general beginner like me can catch up the course with an effort.
the improvement I gain after enroll this course is outstanding
I really appreciate the structure and content of this course. It gave me very good insight into data driven astronomy, programming language (Python), libraries eg NumPy and machine language.
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!
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