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

1,337 ratings

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


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.


Sep 17, 2020

Very Nice course, materials well explained though the programming exercises were very difficult for me, as I did not had that much in depth knowledge of python, for which I had to take additional help

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1 - 25 of 382 Reviews for Data-driven Astronomy


Mar 6, 2020

I have been an astronomy addict since I was a teenager; but, thinking about money, I had a computer science background. Now that I found out the wonderful universe of data science and specially its connection to how astronomy can progress with it, I think i'm completely back to studying our wonderful universe.

By Ayush N

Oct 21, 2018

I finished this course today. If you want to learn advanced concepts like machine learning, decision tree classification, SQL, and more; then this is the course for you! I'm a senior in high school, and I'm going to major in Astrophysics. If you love Computer Science this will be an interesting course, as it will show the applications of CS to Astronomy.

By Robert G

Nov 30, 2020

A great deal of effort went into designing this course. My hat is off to the instructors who designed and participated in this course as well as the mentors who were deep in the weeds with us on our code. With a great deal of effort on your part you will learn a lot.

The single largest issue in data driven astronomy is managing and analyzing enormous datasets. From the very beginning, you will learn about scaling algorithms up to process the size of the datasets efficiently. This is a major theme in computer science.

You will learn a great deal of astronomy from exoplanets to galaxy morphology. The material is sophisticated and does not patronize you the student. It is difficult and rewarding!

My knowledge of Python is rusty as I have been focusing on R for the past year. You will learn more Python, NumPY, matplotlib, and Astropy modules.

The lectures are well thought out and deep. The instructors made interesting comments about the nature of science and the challenges of astronomy.

The bonus interviews with astronomers are not to be missed. The astronomers involved drop great tips about science, the field as it is as well as its recent history.

Answers to the quizzes are not entirely contained in the videos. As a consequence I've either had to think hard about the answers or research the material further--both activities are worthwhile.

Datasets are provided to further pursue the topics in the course, something I fully intend to do. The k-d algorithm is passed off to a AstroPy module--I think it could be done from scratch.'

Careful attention is given to the details of the statistical issues--training and test datasets, asymptotic theory of binning data to obtain medians, etc.

Its all good!

If I had any suggestions to make, it would be to encourage writing up the results of the analyses--giving the student the opportunity not just to celebrate successful code, but to understand the results as well.

By Rodney B

Dec 28, 2020

Fifty-five years ago, as a school leaver about to go to University to study physics, I switched on the television in the middle of the day - when there was nothing showing in the programme schedule printed in the West Australian. To my surprise, instead of either a 'test card' or 'RF noise', there was a lecture being given by a professor, visiting from the UK, as part of the 'Sydney Summer School of Science'.

Wow! Here was exciting and informative educational television on an Australian commercial TV channel, showing at the same time every day for over a week but with no publicity. My awareness of big questions in physics took a great leap forward - by accident.

Fast forward 65 years. A recent occasional glance at Coursera's menu of courses in physics came up with 'Data Driven Astronomy' from the University of Sydney. Being locked down due to Covid-19, I ventured into the first week of the course. What a surprise! I couldn't stop following it - all day, every day for several days running.

Thank you, University of Sydney, for raising my awareness yet again about current big questions in physics (astronomy) and how they can be addressed with big data and an impressive toolkit.

By Gautam D

Dec 3, 2017

First few weeks are challenging, from the coding point of view, but the knowledge that one gains about our Universe is simply fantastic. I've never enjoyed using a Programming language to solve, even though at a beginner's level, problems up until this class. Simply fantastic. If you're curious about Deep Learning, like I am, and are an aspirant in the field of Machine Learning, I highly suggest this course if you're trying to work your way around beginning your journey in Python. I'm proficient in R.

I can't believe this but I've always loved Astrophysics. After 6 years of education and getting a Master's in Industrial Engineering, this course has reignited my love to study our Universe. I will be hungry for more and will be returning to school in the near or distant future for a degree in Astrophysics. Thank You, I love Physics and I really wish I didn't waste my time pursuing what I did pursue.

By avinash

Jun 21, 2018

This is a well set course. I have completed one week and I loved blend of maths, astronomy and tools!Course content is not outdated, which is really important for a field like this.

By riccardo c

Jun 20, 2020

The course is very simple for someone that work as a programmer in data science. Nevertheless is very interesting for who haven't seen astronomical data and want to do some short analysis.

By Max H

Apr 14, 2018

Dr Tara Murphy is exceptionally good at extracting and compressing essential informations and transporting it to the audience. A very well structured course with phantastically produced short movies about basic astronomy topics on an introductory level (great fun to watch this powerthirstesque kind of galactic round-house kick) Reveals some very important fundamentals you should know about scientific computing, introduces you to some of the really hot public scientific libraries, and, eventually, adds some GROK platform learning experience which is unparalleled. There's only one downer (two if you add Dr Simon Murphy's noctilucent shirt in his first lecture): it only scratches a few microns of that nasty double-headed science dragon. Don't expect to to be able to solve problems on the scale of the real world, er... universe with the obtained knowledge. Nevertheless, great job Data-driven Astronomy team!

By Arnaud D

Aug 18, 2018

This is real astronomy ! A fantastic approach to current research subject. If you want to learn astronomy from the ground up, take an introductory course before this one. It starts directly to studying pulsars statistics, and most important, how to detect and study it. All the worshops are in Python, using a web notebook. But it's neither an introductory course on Python. So, it' better to have a minimum knowledge on programming and Python language. But, if you have the prequisites, and are interested to do computation for astronomy using large datasets, this is the course. The techniques can also been extended to other computational intensive domains.

By Gabriel A

Mar 4, 2020

Excellent course that provides an introduction to astronomy from a data analysis point of view. The concepts of astronomy that are touched in this course are not very deep. However, they are well chosen so that the course can be done without any problem. On the other hand, the concepts of data analysis and machine learning are very well explained, so that what you learn here will serve as a basis to face new learning challenges. As I said, just excellent!

By Diego F R M

May 31, 2022

It is a course that I have taken with great pleasure. My background in Astrophysics and my work as a data scientist in private enterprise give me some qualified opinion to say that it is a very well done course. It touches on the basic Python programming topics that will be used, exemplifies with real data the use of data science in solving relevant questions in Astronomy. I also liked the interviews with scientists who use these tools and their opinions about it. I would have loved to have a course like this at my university. Recommended from every point of view, as an introductory course where data analytics meets Machine Learning and the exploration of the Universe.

By james h

Mar 20, 2020

I enjoyed the course. I felt this was a data course with an astronomy wrapper, which is great, because the data portion is applicable way beyond astronomy. The course provides a good intro into numpy (a super useful python library) and sklearn (a super useful machine learning library). I would take this course again.

By Andrew U

Feb 13, 2020

This is a great course combining interesting topics in astronomy with corresponding python challenges. Numpy, SQL and machine learning are all covered here in an astronomy context, though it's easy to see how the same techniques could be applied to other fields.

By Olivier D L

May 14, 2023

Great hands-on introduction to what it means to be an astronomer these days ("the telescope is the data")!

Had a good time solving the exercises, learning the theory, and discovering the many references provided.

Well done, great job!

By Meg D

Mar 29, 2020

Very interesting course that offers plenty of practical applications and insights into data handling for astronomy. It sparks the interest with interviews of experts and additional material on the astronomical topics studied.

By Soumil K

Sep 11, 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.

By Thalia J S

Dec 15, 2019

This is a great course for anyone wanting to do data science with astronomical datasets. The lectures are clear and interesting and the activities are well structured. I really enjoyed this course!

By João P M

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!

By Maria S

Apr 9, 2020

Best MOOC I've ever done. Great for anyone interested in astronomy and/or machine learning.

By Eric H

Oct 28, 2020

Very delicately designed course

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 Shruti P

Jun 9, 2020

I liked the course. Although I feel like if the course was longer and more extensive, I could have learnt a lot more. There aren't many courses that guide one in astronomical data analysis and I have a lot more to learn now.

By Peregrine D

May 13, 2019

A decent introductory course. The weeks follow themes and are not indicative of a suggested timeline.

By Tomas M

Oct 24, 2020

This course pretty much restored my faith in the online courses. Hands down, this is the best online course I have ever had, not only in astronomy. This course had everything to satisfy my needs:

*I had an opportunity to analyse actual astronomical data, which made me feel like a small child again

*I have learned to program in python for scientific reasons, which I previously only used for the backend purposes. The python skills also helped my in my computer modelling studies at the university.

*Also, even though I am working with SQL pretty much every day, this course still managed to teach me some new concepts, and understand joins better. This course, even that it's on the astronomy, managed to explain SQL much better than the conventional lectures.

Regarding the lecturers, both lecturers seemed extremely passionate in what they are talking about, and also managed to explain everything in very concise manner.

Also, I really enjoyed the quizzes, since they do not directly ask what was mentioned in the video, but the questions are twisted a bit to make you actually think for answer.

Finally, this course presents a lot of further research to investigate yourself. This ranges from scientific papers to the links to classify galaxies.

Overall, in my opinion, this course was truly amazing and made my weekends (that's when I had some time to do the exercises) worthwhile. Would definitely recommend it to anyone starting their journey in astronomy, astronomical data, python programming. If you are quite familiar with machine learning concepts and python though, this course might be a bit too easy for you. Though actual astronomical data might spice things up a little.

By Jerome L

Oct 16, 2017

I really enjoyed this course. It is very well structured, with a good progression in the complexity which make it accessible even for people who have quite no skills in Python or SQL, and who are no astronomers (like me). The teachers use a wide range of astronomical subjects to illustrate the different techniques used in data analysis. They propose examples and exercises based on real datasets, which is fabulous for people like me who don't have access to such datasets (or can have access to, but no comprehension of what they show).

Teachers are also reactive in the forums, which is much appreciated. And, for a non-english speaking person, the subtitles are very usefull. The Grok interface is incredibly easy to use, with, again, a progressive complexity in the exercises, and great explanations at each step.

If I tried to find something to improve, I would say: make more obvious how the learned techniques can actually help and improve astrophysical research, maybe with more examples of publications or concrete results obtained in the research field. But it's just quibble over details :-) The interviews in the bonus are very interesting.

So, congratulations for this great work, and thank you for opening a little bit the door of your laboratory :-). Now, more than ever, I hope to work in this domain one day.