Chevron Left
Zurück zu Data-driven Astronomy

Bewertung und Feedback des Lernenden für Data-driven Astronomy von The University of Sydney

4.8
Sterne
1,188 Bewertungen

Über den Kurs

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....

Top-Bewertungen

SK

10. Sep. 2020

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.

MC

28. Feb. 2020

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

Filtern nach:

51 - 75 von 347 Bewertungen für Data-driven Astronomy

von Ondrej M

•

16. Mai 2019

von Nazarov A P

•

17. Juli 2017

von ÁLVARO N J H

•

19. Aug. 2019

von Javier H

•

27. Aug. 2020

von H S

•

16. Juli 2020

von Roger H

•

14. Juni 2020

von Amit K

•

19. Mai 2020

von Alexei M

•

11. Aug. 2017

von Andre R

•

1. Okt. 2020

von Akash P

•

10. Sep. 2017

von Samrat M

•

16. Jan. 2019

von Fausto B d S T

•

3. März 2021

von Egor Z

•

10. Dez. 2019

von Juanu H

•

25. Jan. 2019

von Harshna G

•

22. Juli 2020

von Ahmad S

•

21. Juni 2020

von Alan S

•

19. Apr. 2017

von pascal l

•

15. Dez. 2019

von Lanz A L

•

24. Sep. 2020

von Aura R

•

29. Sep. 2020

von Harish K

•

29. Dez. 2020

von vishwapriya g

•

17. März 2020

von MANAS K

•

28. Dez. 2021

von Qingxiang C

•

18. Juli 2020

von Thiago C L M

•

7. Juni 2020

Coursera Footer

Starten oder fördern Sie Ihre Karriere

Beliebte Themen durchsuchen

Beliebte Kurse und Artikel

Abschluss oder Zertifikat online erwerben

Coursera

Community

Mehr

Überall lernen
Placeholder
Placeholder
Placeholder