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

It's a good start point if we want to understand actual astronomy and the analysis of new big surveys like SDSS or the next LSST

Great course, does help to have a background in python so more time can be spent on the activities.

Really interesting course.

I now need to make further study of the techniques introduced on this course.

It is a really well done course, 100% recommended. Simple but with a lot of information to shared. exercises are really well build in order to anyone can understand the main objective (Astronomy and Machine Learning techniques).

Great lectures, interactive coursework, and easy to understand yet overwhelmingly powerful concepts! Lovely!

It's a nice and short intro to both astronomy and analysing data with python. For me it was a too short because I would like to learn more about this topic, but totally worth it.

Excellent course both on data analysis and astronomy !

Excellent course. One of the best things I learned is that I need to learn statistics now.

Such a wonderful course. It had a very good mix of astronomy and computer science. The programming activities were especially good and the lectures were very informative. I highly recommend.

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

Overall the course is great, I highly recommend it to astronomers who want to learn some new tricks in data science. Meanwhile, it is not so useful for everyone else - lections are super brief and superficial, coding assignments are very easy and not challenging at all, not only you have a pretty self-explanatory template (do A, do B), but it is possible to view a complete solution right away, which is rather strange approach.

I've really enjoyed this course! There are a lot of new things to learn in it. Just to say something not so good from my point of view is that in the exercises sometimes the libraries or code to use could be a bit more explained or documented. But in general it's very good. I recommend it.

So far, the first week has been interesting. Challenging because I am new to Python (I am a C/C++, Swift and ABAP developer) . The assignments are well guided - challenging but far from impossible.

I would like the videos to be a little longer or give a little more theoretical background but mostly it has the right amount of info.

This course lies in the confluence of both my professional experience (software development in the IT industry) and the science that interests me the most: astronomy and astrophysics. Just a glance at the syllabus was enough to convince me that the course would be worth taking, due to its good structure and wide scope, covering current trends in both data science and computational astronomy.

From previous online course experience in these areas, I knew at the beginning that contents can be hard to grasp if the theory and practice are not well balanced, but it turned out to be a great run, with enough depth to pique one's interest while at the same time feeling comfortable using both past and newly acquired knowledge.

The course sports an excellent tool to solve and test the programming assignments that constitute most of the grades you will earn. Thanks to it, you will be freed, as a student, from the most common hassles in online courses involving coding (mainly environment setup). Which means more chances to focus on the main subjects covered and a pleasant wading through the challenges posed.

Beware that if you are already comfortable ín the programming language used (Python), you may easily be craving for more advanced assignments, but this I'm sure is easy to request from the helpful professors and staff. If you are instead a novice with regards to coding, additional parallel effort may be required, but the course contents will guide you well in the endeavor.

One aspect of the course that may be specially challenging is the relatively speedy run through the theory and concepts of Machine Learning. A myriad other online courses on the subject exist already; the course focusses instead more on the application of the techniques and nicely shows real world (or more appropriately, universe :-) ) applications which will help cementing the theories behind. I would expect that if you have not had previous contact with the subject, the contents can feel a bit daunting. But with some extra commitment (check the numerous online resources, take a parallel course...) I am pretty sure this can be overcome.

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

Good course, with fun examples to work with. I'm not an astronomer, and mainly took the course for fun,but the things I've learned here will be useful for my own research. About the only thing I would have liked to see was more background material on each topic.

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.

I thought this class was a great application of Python Programming to an interesting topic that I otherwise would not have learned. However, coming from a computer science background, the programming was pretty easy. If you are looking to strictly learn more about programming, I would suggest a more difficult course.

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!

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.

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

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