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.

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 I have completed one week and I loved blend of maths, astronomy and tools!Course content is not outdated, which is really important for a field like this.

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!

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.

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!

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.

I highly recommend this course if you are curious about some of the big data tools and techniques used in astronomy. Especially if you already use Python a bit and want to try out some machine learning and other astronomy related python tools. I wanted to learn something about astronomy and to play with the data - the cross-matching and machine learning were my favourite parts of the course. As usual, I'm in awe about what we know about the universe - so to casually play with data on Active Galactic Nuclei for example, or redshifts of galaxies was great fun, educational and just brilliant. I've got things I want to try out now, before starting another course. Oh, and the two tutors present the material very well on the videos.

This is a very interesting introduction to data analysis and machine learning for astronomy. The hands-on approach makes the course quite engaging.

The course is well structured and presented. The lectures are interesting and the explanations clear. The course materials are well chosen to illustrate what is being taught in the lectures. The development environment (Grok) is usable and glitch-free.

The choice of programming language, Python3, looks quite right to me. Python has become the "new normal" in astronomy. It offers an easy learning curve and a myriad of well tested modules which are available for free.

I really enjoyed this course and I would recommend it to any one with an interest in this or related subjects.

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.

Just finished this wonderful course, it teaches (mostly in Python) the basics of how to apply certain techniques of data handling, processing, and analysis, in the realm of Astronomy, which has vast amounts of collected data and which I've loved all my life as a hobbyist! This knowledge is very useful and can be extended to many other scientific fields. The course has a great mix of theory and hands-on exercises (with a great supporting online coding platform), and encourages people to continue reading and experimenting on their own.

First, I enjoyed the course, thank you. I am a computer scientist by profession, and came here to learn how astronomers perceive data analysis software in their pursuit. This course not only introduced me to how software is used for data analysis in astronomy, but also gave me insights on challenges the community is (or could potentially be) facing. Course is well-paced on theoretical and programming fronts, along with necessary hand-holding whenever required. Hoping to see an advanced version of this course. Thank you again.

It's been an amazing and educative journey. Besides sharping my Python skills, the Astropy and Numpy library are really a wealth of knowledge that is worth using. Machine learning was new for me, specifically decision trees. I got some knowledge 20 years ago about neural networks and fussy logic, but his was something new. All in all, the instructors and assisting staff showed their expertise both in the programming part as well as in the astronomical domain. Really a recommended course for those who love both domains!

I enjoy learning about recent advances in astronomy. Since astronomy isn't my vocation, I usually have to settle for a view from the sidelines. Although that may still be the case, I think this course has taken me to a seat in the front row. Moreover, I learned computational thinking, which is immensely useful in my vocation. I couldn't have asked for a better way to marry my love of astronomy with practical knowledge of modern day tools to extract, store, and manipulate data and glean useful insights from the data.

I enjoyed this fusion of programming with Astronomy topics. Note that the exercises use the Python programming language (no substitutes permitted), fairly generic Structured Query Language (SQL) for databases, numpy (science math tools) Python library, scikit-learn (machine learning) Python library, and matplotlib (math & plotting) Python library.

I highly recommend this course, even if you are already experienced in a subset of the above.

Would be interesting: a 2nd more advanced course.

What I liked about the course was the graded programming assignments, which help to introduce a person to machine learning techniques and other problems in astronomy data processing. Being a physics student by formal education and a star gazer too, I am familiar with the theory but was always curious about how to they measure distances, how do they measure red-shifts etc when the distant galaxies are themselves so faint. This course helped me understand these stuff....

Thank you for a very interesting, educational, and ofttimes challenging course. I suspect the instructors and mentors have introduced me to only the tip of the iceberg - 98% of data-driven astronomy lies below the surface and inside enormous datasets/databases. It almost makes me wish life had taken a different course and brought me to this fascinating subject. I would look forward to any further courses from you.

One of the best courses I have taken. The instructors are fantastic! This course is like a 500 page novel that you cannot put down and now you are on the last 10 pages. I do not want this course to end!! It was such pleasure to go through the videos and problems!!

Sincere thanks to Professor Tara Murphy and Dr. Simon Murphy !! Good on ya mates!! Please have a follow-on course!!

A solid, compact, no-nonsense introduction to machine learning in Astronomy using Python's rich scientific tool sets. I think the knowledge will help equip the learners to straight away apply some of the skills in practical scenarios not only in Astronomy but also in other ML scenarios. A delicious Apple pie of Computer science, Astronomy and Programming served in a bite sized fashion.

I absolutely loved this course. I can honestly say this is my favorite class I've ever taken. What a perfect blend of real astronomy, programming, Python, SQL, machine-learning, and data analysis. Thank you SO much for creating/curating this course, and for all the mentors for their help and insight. I wish I could do this type of work for a living. Well-done!! Five stars.

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.

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.

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

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.