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Learner Reviews & Feedback for Data-driven Astronomy by The University of Sydney

4.8
stars
923 ratings
276 reviews

About the Course

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 reviews

SK
Sep 10, 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
Feb 28, 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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251 - 273 of 273 Reviews for Data-driven Astronomy

By Roberto G

Jun 30, 2020

Very interesting approach to astronomy, although I would have preferred larger part of the course devoted to strictly astronomical topics and less time spent on basic quantitative notions. By the way, thank you, you gave me some hours of enjoyment.

By Archana B

Jul 10, 2020

An amazing course to get started for someone like me, passionate about astronomy and closely related to the field of computer science. Very well organized and nicely explained course with great visuals and mid-tests. Kudos to the instructors!

By K S R

Sep 25, 2019

A really good course covering a variety of subjects in both astronomy and data analysis which is exactly the combination I was looking for. A final exercise covering all the topics taught would have been a fitting end to the course.

By Vibha

Dec 8, 2019

Well-taught, good supporting resources, and heavily rooted in application. The external grading tool exceeded expectations as well. Next time, would prefer more of the code being explained by the instructors.

By Federico T

Jul 24, 2017

A good introduction in Data Astronomy with Python. I missed some lessons about python to finish some of the volunteer exercises and some contact with astronomy data from the web, but it is a great course.

By Gautam B

Apr 21, 2017

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!

By Francisco

May 15, 2019

Interesting introduction to machine-learning techniques applied to astronomical data. I think very adapted to astronomers willing to learn about this topic or to astronomy students.

By GAVIN W

Sep 29, 2019

If you want to learn Python and a bit of Machine Learning in the context of Astronomy then this is a great course to give your skills a boost and learn more about modern Astronomy.

By José L I M

Jul 29, 2020

I've been researching on both machine learning and astronomy, this is a nice course to get introduced on how things are being made in data-driven Astronomy.

By John I

Aug 31, 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.

By Ayush R

May 15, 2020

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

By Ignacio d L A G

Dec 27, 2019

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

By Anand K

Jan 31, 2020

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

By Alastair K

Jan 7, 2018

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

By Rita A

Jul 10, 2020

This course involved a brilliant interplay between theory and application !

By Harsh T

Apr 8, 2020

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

By Jordi G P

Dec 10, 2018

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

By Enrique J E B

Sep 8, 2019

Nice introduction to machine learning using an interesting topic.

By Antariksha M

Sep 10, 2019

Great Learning

By Andrew L

Oct 19, 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!

By Robert N

Nov 25, 2017

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

By Shalini s

Jun 17, 2020

actually i wrongly pressed this course and its not unenrolling