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Kursteilnehmer-Bewertung und -Feedback für Data-driven Astronomy von The University of Sydney

905 Bewertungen
271 Bewertungen

Über den Kurs

Science is undergoing a data explosion, and astronomy is leading the way. Modern telescopes produce terabytes of data per observation, and the simulations required to model our observable Universe push supercomputers to their limits. To analyse this data scientists need to be able to think computationally to solve problems. In this course you will investigate the challenges of working with large datasets: how to implement algorithms that work; how to use databases to manage your data; and how to learn from your data with machine learning tools. The focus is on practical skills - all the activities will be done in Python 3, a modern programming language used throughout astronomy. Regardless of whether you’re already a scientist, studying to become one, or just interested in how modern astronomy works ‘under the bonnet’, this course will help you explore astronomy: from planets, to pulsars to black holes. Course outline: Week 1: Thinking about data - Principles of computational thinking - Discovering pulsars in radio images Week 2: Big data makes things slow - How to work out the time complexity of algorithms - Exploring the black holes at the centres of massive galaxies Week 3: Querying data using SQL - How to use databases to analyse your data - Investigating exoplanets in other solar systems Week 4: Managing your data - How to set up databases to manage your data - Exploring the lifecycle of stars in our Galaxy Week 5: Learning from data: regression - Using machine learning tools to investigate your data - Calculating the redshifts of distant galaxies Week 6: Learning from data: classification - Using machine learning tools to classify your data - Investigating different types of galaxies Each week will also have an interview with a data-driven astronomy expert. Note that some knowledge of Python is assumed, including variables, control structures, data structures, functions, and working with files....



Sep 11, 2020

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.


Feb 29, 2020

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

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51 - 75 von 269 Bewertungen für Data-driven Astronomy

von Andre R

Oct 01, 2020

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.

von Akash M P

Sep 10, 2017

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.

von Samrat M

Jan 16, 2019

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.

von Egor Z

Dec 10, 2019

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).

von Juan M H

Jan 25, 2019

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!

von Harshna G

Jul 23, 2020

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!

von Ahmad S

Jun 21, 2020

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.

von Alan S

Apr 19, 2017

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.

von pascal l

Dec 15, 2019

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.


von Lanz A L

Sep 24, 2020

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.

von Aura d l E R A

Sep 29, 2020

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.

von vishwapriya g

Mar 18, 2020

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.

von Qingxiang C

Jul 18, 2020

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.

von Thiago C L M

Jun 07, 2020

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.

von Daniel H

Sep 25, 2020

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.

von Utkarsh T

Nov 21, 2019

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.

von vas m

Aug 26, 2020

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.

von Barun S

Jun 11, 2020

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.

von Athul

Jun 07, 2020

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

von Nabanita R

Jan 24, 2020

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.

von Erik v P

Sep 05, 2017

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.

von Johanna B

Feb 26, 2020

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.

von Jesse S

Aug 30, 2017

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.

von Manoj J

May 30, 2019

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 !!

von Avinash C

Feb 10, 2020

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.