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Volver a Data-driven Astronomy

Data-driven Astronomy, Universidad de Sidney

4.8
361 calificaciones
104 revisiones

Acerca de este Curso

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. Regardless of whether you’re already a scientist, studying to become one, or just interested in how modern astronomy works ‘under the bonnet’, this course will help you explore astronomy: from planets, to pulsars to black holes. Course outline: Week 1: Thinking about data - Principles of computational thinking - Discovering pulsars in radio images Week 2: Big data makes things slow - How to work out the time complexity of algorithms - Exploring the black holes at the centres of massive galaxies Week 3: Querying data using SQL - How to use databases to analyse your data - Investigating exoplanets in other solar systems Week 4: Managing your data - How to set up databases to manage your data - Exploring the lifecycle of stars in our Galaxy Week 5: Learning from data: regression - Using machine learning tools to investigate your data - Calculating the redshifts of distant galaxies Week 6: Learning from data: classification - Using machine learning tools to classify your data - Investigating different types of galaxies Each week will also have an interview with a data-driven astronomy expert. Note that some knowledge of Python is assumed, including variables, control structures, data structures, functions, and working with files....

Principales revisiones

por GM

Jun 30, 2017

Great course with a good balance of code and the rewards to be had from understanding how the code works - proved to be an excellent introduction to Astronomy and confidence builder in Python.

por JM

Jul 15, 2017

One of the best courses I've done on Coursera. Just enough astronomy to understand the problems, and then go into the exercises in a step by step way, building up complexity. Couldn't stop!

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102 revisiones

por Ananth S

Apr 24, 2019

Wonderful course and loved every bit of it. My only concern is that I would love to have some form of a certificate even though I can not afford to pay for the course.

por 唐怀金

Apr 23, 2019

very good

por Afiq Abdul Hamid

Apr 22, 2019

Good stuff. Thanks Coursera.

por Sara Doan

Apr 08, 2019

Fantastic! I learned a lot. The exercises were really interesting!

por Richard Osseweyer

Apr 01, 2019

Perfect to brush up my Python skills while studying a fascinating subject!

por Daniel Nájera

Mar 20, 2019

very good course, with clear technical explination and interesting

por Mark Murray

Mar 18, 2019

Interesting, engaging and informative!

por miguel andrade

Mar 09, 2019

Fue un excelente curso , me ayuda mucho para poder intentar el procesado de unos catalogos de galaxias en especial la parte del machine learning aplicado

por Michael West

Mar 08, 2019

This is a very well organized, interesting, and, quite frankly, fun class. I especially liked being able to do hands-on exercises in Python.

por Atul Nanal

Feb 09, 2019

What I liked about the course was the graded programming assignments, which help to introduce a person to machine learning techniques and other problems in astronomy data processing. Being a physics student by formal education and a star gazer too, I am familiar with the theory but was always curious about how to they measure distances, how do they measure red-shifts etc when the distant galaxies are themselves so faint. This course helped me understand these stuff....