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.
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
By Javier H•
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.
By H S•
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.
By Roger H•
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.
By Amit K•
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.
By Alexei M•
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.
By Andre R•
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.
By Akash P•
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.
By Samrat M•
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.
By Fausto B D S T•
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!
By Egor Z•
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).
By Juan M H•
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!
By Harshna G•
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!
By Ahmad S•
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.
By Alan S•
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.
By pascal l•
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.
By Lanz A L•
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.
By Aura d l E R A•
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.
By Harish K•
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.
By vishwapriya g•
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.
By Qingxiang C•
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.
By Thiago C L M•
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.
By José Á F G•
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.
By Daniel H•
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.
By Utkarsh T•
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.
By vas m•
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.