Although, I gave a five star, but I have following notes:

It was brilliantly structured on shaping and combining scientific problems with data science to tackle those issue. However, it could use few more examples to add to our current skills. Thank you again. That was the course I was looking for, after taking a course on Machine Learning by Andrea NG, from Stanford University.

This course was absolutely fascinating, thank you so much! I especially enjoyed the discussions about actually thinking through the data instead of just jumping in with whatever tool or algorithm you normally use, loved the short astronomical overview pieces and their quizzes, and the bonus material - interviews of people working in the "real world" out there - was great.

Great Course! The practice section on Grok platform is what makes it especially good, considering you don't really need to setup a programming environment on your own machine. Additionally, each module has a very interesting problem, that you dive into to create a working solution step-by-step to obtain a visible result, which is satisfying and encouraging to go further.

I have enjoyed fully the whole course which helped me to connect my professional skills in coding and data analytics with my hobby - astronomy. The lectures were clear, very well understandable, motivated me to make my own research and the Grok platform is very well suited for getting the "hands on" experience. I also appreciate links to external tools and data sources.

Enjoyed this course a lot - nice introduction to some of the python techniques used.

I have a decent background in astronomy and astrophysics but that isnt really necessary. This is a good run through the various different approaches to both access, store and analyse data while framing this around galaxy classification that builds as you progress through the course.

Very good intraductional course to modern astronomy that is nowadys more and more science about data. Not so much astronomy theory but good programing tasks, sometimes challenging, especially in the starting weeks. As addition some introduction in machine learning is provided. I would recommend it to everyone interested in data analysis in modern science.

Un curso introductorio, de dificultad variable (quizás más duro al principio que al final) muy interesante tanto para enlazar teoría y práctica en el campo de la Astronomía, para iniciarse en las técnicas y conceptos clave del Machine Learning, como para desarrollar o refrescar el pensamiento algorítmico-computacional.

En resumen: MUY BUEN CURSO

Very good course for anybody, with a knowledge about programming with Python and without them, im a engineering student and i love the modules to plot beautiful variables relation graphics and finding the more important values on a big source of data. Qualified teachers and a interesting application to use Python and learn at the same time.

The practical approach really enabled me to learn more. Instead of just lectures and quizzes, the programming problem sets challenged me to properly learn different features of python. Since I am new to programming, I had to use a lot of outside sources to complete the code. I had to engage significantly more with the problems posed.

Very enjoyable and practical dive into astronomy concepts. I think the machine learning part could have been a bit more advanced but now I understand it is meant to be an intro-level practical tutorial in both machine learning concepts/data science concepts and how they apply to astronomy. In this respect, the course does quite well.

The course, video, practice, all are really good. But one who is joining this, really need good python practice and knowledge of astronomy. In the discussion forum it may take some time but reply comes. I’ll suggest for making it better further. It is really awesome. One join the course and take advantage of it. Thank you all.

A great place to get hands dirty for those who are interested in how modern astronomy handles and does science with observational data. Good for both amateur astronomers and professionals. I enjoyed the course very much. Impressive is how practical part of programming was made available and worked smooth most of the time.

One of the best online courses I've taken. Dr. T is an excellent communicator. Course is nicely chunked to make it challenging, yet encouraging. First data science class I've taken in which the datasets are interesting - not simulated, no flower petals or handwriting. Fingers crossed for DL class from these instructors.

Most of all courses in astronomy and astrophysics are just introduction to subject or provides little advanced theoretical perspective but this is one of the courses which teach us practical astronomy and let us have insights of how astronomers really use physics as well as computers to to get something good out of it.

The course was just epic. Anyone who wants to learn about the application of Machine Learning in the field of Astronomy , this course is a must. The activities will be like the instructor is sitting just by your side, and guiding you, which is what any beginner wants to start their journey. The course is just awesome.

I just can't thank the staff enough for the effort in making this high quality course available. It was an amazing learning experience.

If you want to learn about some of the most amazing aspects of our physical universe while having fun with python and machine learning, just go for it! It is definetely worth it!

Amazing course about the Sky above. Here is python code practice with NumPy and Astropy libraries - very useful for me.

But, I didn't understand that guy, just at the end of 2nd week talking. Little bit boring stuff. I think better to show the beauty of the astronomy data in visual aspect and more (in sound).

Besides being a Senior Developer, and Junior Data Scientist, I also am a Self Taught astronomer, and this course has given me a lot of knowledge and insights about astronomy, andways in which I can practice my self learning carrear in astronomy (and maybe astrophysics?) Awesome course! Highly recommended!

Such a great introduction course to data-driven astronomy! As someone working full-time the fact that it was only 6 weeks length - meant that it was easy to complete! Tara and Simon are great at explaining concepts and the interactive tool for python/SQL provides real-world example problems! Loved it!

Just AWESOME! I absolutely loved. Great staff, fun syllabus. I'd recommend it to anyone with a CS background seeking a look on how beautiful the universe is (if you're already bored with pop-science videos.) The most surprising thing about the MOOC actually is how integral CS is to modern astronomy.

A very interesting course, even though I am not an astronomer. Plenty of examples on the use of Python for data handling, ML classification of astronomical objects (sklearn), plus a neat section on RDMS usage (postgresql + python). Many thanks to all at astro-sydney for their help and Coursera.

Thank you for this course. I come from a technical background and this course feels tailor made for me. It is a great introduction to astronomy, Python, Sql and Mtl. It is put together very well and the exercises feel like a hands on session. Enjoyed every bit of this learning experience.

I am a astronomy amateur observer - having attended this course provided me a totally different approach to existing image analysis programs - I can now preview what will be the future of pro/am collaborations...

Thanks again for the quality of this course - truly accessible to all.

Pascal

This is the perfect introductory course for anyone who has a good python skillset and the desire to further enhance this in order to work on leveraging them effectively for astronomy research. Now, I have confidence to finally access the GAIA DR2 database using Python and SQL/ADQL.

Excellent course!! really interesting and enjoyable. It gives an overview of both data science skills and varied but fundamental astronomy concepts. As a professional astronomer I loved it, and learned a lot about some types of algorithms that are useful in data driven astronomy.