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

4.8
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540 Bewertungen
170 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

TS

Dec 15, 2019

This is a great course for anyone wanting to do data science with astronomical datasets. The lectures are clear and interesting and the activities are well structured. I really enjoyed this course!

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.

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126 - 150 von 167 Bewertungen für Data-driven Astronomy

von David B

Nov 02, 2017

Very enjoyable and at times challenging.

von Mark M

Mar 18, 2019

Interesting, engaging and informative!

von Rodrigo J

Aug 12, 2017

Fantastic and concise hands-on course!

von Ernesto P

Sep 28, 2017

Great course and very good material

von Ujjwal J

Jun 13, 2019

best course i ve taken in coursera

von Behzad B A

Jan 27, 2019

Very professional, very productive

von Sachin V

Sep 29, 2019

extremely multidisciplinary!

von Afiq A H

Apr 22, 2019

Good stuff. Thanks Coursera.

von Luciano S

Jun 11, 2017

It was an amazing course!

von Ulisses M C

May 17, 2018

The course is excellent.

von hawzhin b

Aug 24, 2018

Very useful course ,

von Sviatoslav S

Jan 06, 2018

Excellent course! =)

von Yasith R

Jun 10, 2019

Excellent course..

von Diego J M G

Jan 14, 2019

Muy recomendable

von Syed Z R Z

Jan 18, 2020

Its gerearatttt

von Rohit N

Jun 12, 2019

I'm loving it!

von Jiqing H

Jun 12, 2019

great course!

von Israel d S R d A

Feb 07, 2020

Very helpful

von 唐怀金

Apr 23, 2019

very good

von Kristina I

Apr 19, 2017

Excellent

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 Tomislav P

Jan 27, 2020

Generally, I liked the course and really enjoyed it; I think it is really well made. However, I decided to give it 4/5 stars, because it is a bit short, covers only a small part of astronomy and machine learning and because exercises are not that challenging and too much help is sometimes given. I'd give it 5 stars if the course was a bit longer (2-3 times as long), covered more astronomy and machine learning topics (with exercises as well), and maybe most importantly forced the participant to go through more materials to be able to finish the course. Nonetheless, I'd like to thank the course's creators!

von Pavel K

Oct 20, 2018

Overall the course is great, I highly recommend it to astronomers who want to learn some new tricks in data science. Meanwhile, it is not so useful for everyone else - lections are super brief and superficial, coding assignments are very easy and not challenging at all, not only you have a pretty self-explanatory template (do A, do B), but it is possible to view a complete solution right away, which is rather strange approach.

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 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.