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

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1,068 Bewertungen
315 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

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301 - 314 von 314 Bewertungen für Data-driven Astronomy

von John I

31. Aug. 2019

I enjoyed the course.

The only issue was with a couple of the python labs not having the data to try within my own environment.

von Ayush R

15. Mai 2020

One of the best courses on astronomy and coding. So thoughtfully created and explained. I would love if y'all do this course!

von Ignacio d L A G

27. Dez. 2019

He aprendido cosas, hasta ahora, desconocidas para mi. Me ha abierto la curiosidad por investigar

von Anand K

31. Jan. 2020

So the course is of introductory type. Not much in depth. Great for beginners in Data Science.

von Alastair K

7. Jan. 2018

great course with practical python programming. very informative and easy to follow

von Rita A

10. Juli 2020

This course involved a brilliant interplay between theory and application !

von Harsh T

8. Apr. 2020

It has been a fantastic journey of Astronomy with actual data and coding.

von Jordi G P

10. Dez. 2018

Pretty good introduction to both Big Data treatment and modern astronomy!

von Enrique J E B

8. Sep. 2019

Nice introduction to machine learning using an interesting topic.

von Antariksha M

10. Sep. 2019

Great Learning

von Andrew L

19. Okt. 2020

The course was interesting, but suffered from being a little to lightweight in both the Astronomy and Data Driven aspects - it probably tries to do too much in a short period of time. If you already have some programming knowledge, esp in SQL or Python, the practical assignments you'll likely find quite easy and can be completed in under half the estimated time. I'd be interested in seeing an advanced version of this course though!

von Robert N

25. Nov. 2017

Sorry, but this course was one of the weakest I have followed.

von Shalini s

17. Juni 2020

actually i wrongly pressed this course and its not unenrolling