Very well designed course. Each week/module introduced a specific astronomical question, and then introduced the data analysis tools to answer the question. This allowed the learner to become familiar both with the question and the tool. The Grok platform was also very helpful.

It is one of the best courses I came across. It summarizes and gives a feel for the data science process and methods along with the flavour of astronomy. The other thing I liked most about the hands-on learning experience. I thank the Instructors and Coursera wholeheartedly.

It is a good course to do for people who have an interest in A&A. The course teaches the use of languages like Python and SQL in the domain of A&A and doing this course, one can start analyzing public databases with this knowledge and contribute to the scientific community.

This is a very nice course. You can gain some interesting astronomy knowledge as well as data processing technique. I found the median stacking, SQL basics and machine learning implementation modules quite useful. Also you can get some experience on python programming.

I highly recommend this course from The University of Sidney. It was very well taught, with a good amount of exercises and excellent videos from top-notch researchers. It is a course for everybody, especially data scientists, analysts, astronomers, and astrophysicists.

Un curso bastante interesante en donde se abordan de manera paralela temas importante en astronomía moderna y técnicas estándar en análisis de datos. Muy recomendable para los que quieran aprender las bases de análisis de datos a través de problemas reales en física.

Data Driven Astronomy course is well paced and the instructors present the material in a way that is interesting and fun. The exercises were useful and at the right level for the course. After each section is an interview with an Astronomer which was very helpful.

The exposure that I needed just to understand how day-to-day things work in professional astronomy has given to me through this course. I am utterly thankful to all the instructors and their respective team for placing such a great quality education in the market.

I found this module a good, for me it was good recap of SQL and python. And introduction to ML, big data and astronomy. Exercises are good to do - they do take some time, to do properly and learn from - some of the ML is more cut and past, using python libraries.

Both of the lecturers present the information in a clear and concise way. If you are used to using an IDE grok has some drawbacks such as not auto completing brackets and quotes; these are easily overcome though. Thanks to Both the Murphys for this opportunity.

I really enjoyed this course which gives basic but solid knowledge of astronomy (providing also hints for further resources) and allows anyone having a basic understanding of python what is needed to kick off with machine learning methods! I'm really thankful!

it is obviously a wonderful course to learn so much about my favourite subjects got good computational skills, Thank you for making this course so easy and understandable, hope I will get more contents like this, Thank you Coursera, thanks to all the faculty.

The course is well defined with clear presentation. From an astronomy prespective, the course provides necessary knowledge for inspiring us to step into data analysis and machine learning. Thank you University of Sydney to host such a course on astronomy

Application consists a lot of basics including using SQL database and programming. This course should be labelled as fundamental. There should another course that emphasises only on the usage and practical applications of ML in astronomical institutions.

I am an astronomy lover and a programmer, for me this course is the first acquaintance with the work of a professional astronomer. It was very interesting thanks a lot! Could you please make an advanced course with laboratory work from real research? :)

Good introduction course to big data. Some prior knowledge of Python is good to have to make it easier to get through the course, The astronomy part of the course is very interesting. It has changed much since I took university level courses in it.

The videos are extremely well-done and contain just the right amount of content for astronomy newbies like me. I really enjoyed the use of Grok. Personally, I don't think previous python knowledge is necessary to successfully complete this course.

Well constructed course, that is manageable by a variety of skill levels. Some background in machine learning is helpfull but the course consentrates on other data management skills as well. I enjoyed it and will be using it for future reference.

Fun, engaging programming-focused assessments with just the right balance of structure and freedom. Diligent mentors such as Magda on the Forums. All embedded in the wonderful content of Astronomy. Good for practising Python and an intro to SQL.

This course is excellent for anyone who loves astronomy and is looking to working in the field .The concepts are conveyed effectively and the assignments are the most important aspects as they teach a lot more than the videos . Its was fun !!

This course was very useful and insightful for me. I really liked the programming sets. I did feel that there could have been bit more detailed discussion in Machine learning part. I would really love to do an advance course in this subject.

Interesting content, great videos that are never too longer or verbose. Nice balance of learning asssessments/quizes and coding expercises. Unique course that does a great job marrying physical science with data science. Highly recommended.

This course has provide me with great insights in the field on Astrophysics. It has really helped in matching my interests in Astrophysics and Machine Learning. Now, I feel confident to play with data from SDSS and Kepler Exoplanet Archive.

Amazing course! I learned a lot about astronomy, quasars, galaxies, machine learning, python and the scientific libraries numpy, scikit-learn, scipy, creating programs that are optimised in memory use and that complete in reasonable time

I'm very happy that i came across this course on Coursera. Even more am I happy that they let me complete this course for free. It showed me how we analyze those tremendous amount of data we receive from telescopes and draw conclusions.