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

4.8
469 Bewertungen
143 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....

Top-Bewertungen

GM

Jun 30, 2017

Great course with a good balance of code and the rewards to be had from understanding how the code works - proved to be an excellent introduction to Astronomy and confidence builder in Python.

BF

Aug 11, 2019

Such a wonderful course. It had a very good mix of astronomy and computer science. The programming activities were especially good and the lectures were very informative. I highly recommend.

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126 - 140 von 140 Bewertungen für Data-driven Astronomy

von Rene F

Sep 04, 2017

So far, the first week has been interesting. Challenging because I am new to Python (I am a C/C++, Swift and ABAP developer) . The assignments are well guided - challenging but far from impossible.

I would like the videos to be a little longer or give a little more theoretical background but mostly it has the right amount of info.

von Victor M

May 17, 2017

This course lies in the confluence of both my professional experience (software development in the IT industry) and the science that interests me the most: astronomy and astrophysics. Just a glance at the syllabus was enough to convince me that the course would be worth taking, due to its good structure and wide scope, covering current trends in both data science and computational astronomy.

From previous online course experience in these areas, I knew at the beginning that contents can be hard to grasp if the theory and practice are not well balanced, but it turned out to be a great run, with enough depth to pique one's interest while at the same time feeling comfortable using both past and newly acquired knowledge.

The course sports an excellent tool to solve and test the programming assignments that constitute most of the grades you will earn. Thanks to it, you will be freed, as a student, from the most common hassles in online courses involving coding (mainly environment setup). Which means more chances to focus on the main subjects covered and a pleasant wading through the challenges posed.

Beware that if you are already comfortable ín the programming language used (Python), you may easily be craving for more advanced assignments, but this I'm sure is easy to request from the helpful professors and staff. If you are instead a novice with regards to coding, additional parallel effort may be required, but the course contents will guide you well in the endeavor.

One aspect of the course that may be specially challenging is the relatively speedy run through the theory and concepts of Machine Learning. A myriad other online courses on the subject exist already; the course focusses instead more on the application of the techniques and nicely shows real world (or more appropriately, universe :-) ) applications which will help cementing the theories behind. I would expect that if you have not had previous contact with the subject, the contents can feel a bit daunting. But with some extra commitment (check the numerous online resources, take a parallel course...) I am pretty sure this can be overcome.

von Alastair K

Jan 07, 2018

great course with practical python programming. very informative and easy to follow

von Doug

Jan 29, 2018

Good course, with fun examples to work with. I'm not an astronomer, and mainly took the course for fun,but the things I've learned here will be useful for my own research. About the only thing I would have liked to see was more background material on each topic.

von Federico T

Jul 24, 2017

A good introduction in Data Astronomy with Python. I missed some lessons about python to finish some of the volunteer exercises and some contact with astronomy data from the web, but it is a great course.

von Adam S

Jun 25, 2017

I thought this class was a great application of Python Programming to an interesting topic that I otherwise would not have learned. However, coming from a computer science background, the programming was pretty easy. If you are looking to strictly learn more about programming, I would suggest a more difficult course.

von Gautam B

Apr 22, 2017

Great and quick way to learn things. Thanks for the troubles taken to put this together. Some of the computational exercises could do with a little more clarity of language. But, overall, Great!

von Francisco

May 15, 2019

Interesting introduction to machine-learning techniques applied to astronomical data. I think very adapted to astronomers willing to learn about this topic or to astronomy students.

von Enrique J E B

Sep 08, 2019

Nice introduction to machine learning using an interesting topic.

von Antariksha M

Sep 10, 2019

Great Learning

von John I

Aug 31, 2019

I enjoyed the course.

The only issue was with a couple of the python labs not having the data to try within my own environment.

von K S R

Sep 25, 2019

A really good course covering a variety of subjects in both astronomy and data analysis which is exactly the combination I was looking for. A final exercise covering all the topics taught would have been a fitting end to the course.

von GAVIN W

Sep 30, 2019

If you want to learn Python and a bit of Machine Learning in the context of Astronomy then this is a great course to give your skills a boost and learn more about modern Astronomy.

von Peregrine D

May 13, 2019

A decent introductory course. The weeks follow themes and are not indicative of a suggested timeline.

von Robert N

Nov 25, 2017

Sorry, but this course was one of the weakest I have followed.