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Opiniones y comentarios de aprendices correspondientes a Data-driven Astronomy por parte de Universidad de Sidney

896 calificaciones
267 reseña

Acerca del Curso

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....

Principales reseñas

10 de sep. de 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.

28 de feb. de 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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1 - 25 de 264 revisiones para Data-driven Astronomy

por Ayush N

21 de oct. de 2018

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.

por Reinaldo L N

6 de mar. de 2020

I have been an astronomy addict since I was a teenager; but, thinking about money, I had a computer science background. Now that I found out the wonderful universe of data science and specially its connection to how astronomy can progress with it, I think i'm completely back to studying our wonderful universe.

por avinash

21 de jun. de 2018

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.

por Max H

14 de abr. de 2018

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!

por Gautam D

3 de dic. de 2017

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.

por Gabriel A

4 de mar. de 2020

Excellent course that provides an introduction to astronomy from a data analysis point of view. The concepts of astronomy that are touched in this course are not very deep. However, they are well chosen so that the course can be done without any problem. On the other hand, the concepts of data analysis and machine learning are very well explained, so that what you learn here will serve as a basis to face new learning challenges. As I said, just excellent!

por James H

20 de mar. de 2020

I enjoyed the course. I felt this was a data course with an astronomy wrapper, which is great, because the data portion is applicable way beyond astronomy. The course provides a good intro into numpy (a super useful python library) and sklearn (a super useful machine learning library). I would take this course again.

por Andrew U

13 de feb. de 2020

This is a great course combining interesting topics in astronomy with corresponding python challenges. Numpy, SQL and machine learning are all covered here in an astronomy context, though it's easy to see how the same techniques could be applied to other fields.

por Maria D

29 de mar. de 2020

Very interesting course that offers plenty of practical applications and insights into data handling for astronomy. It sparks the interest with interviews of experts and additional material on the astronomical topics studied.

por Thalia J S

15 de dic. de 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!

por João P M

15 de jul. de 2017

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!

por Maria S

9 de abr. de 2020

Best MOOC I've ever done. Great for anyone interested in astronomy and/or machine learning.

por riccardo c

20 de jun. de 2020

The course is very simple for someone that work as a programmer in data science. Nevertheless is very interesting for who haven't seen astronomical data and want to do some short analysis.

por Shruti P

9 de jun. de 2020

I liked the course. Although I feel like if the course was longer and more extensive, I could have learnt a lot more. There aren't many courses that guide one in astronomical data analysis and I have a lot more to learn now.

por Peregrine D

13 de may. de 2019

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

por Jerome L

16 de oct. de 2017

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.

por José R S

4 de may. de 2020

Gostei demais das aulas condizentes com a posterior apresentação do conteúdo e aplicação dos exercícios. Acredito que alguns deles contém alguma falha na avaliação como uso de funções que não foram apresentadas, isso implica que um estudante atento possa pensar que não pode usar aquela função (como uma trapaça) ou mesmo um estudante ainda leigo na específica tarefa. Acho isso um probleminha pontual e que não interferiu de maneira alguma no aprendizado, afinal, a solução está lá para ser verificada.

O conteúdo é bem abrangente e aborda de maneira geral uma gama interessante de assuntos da astrofísica. Achei que no começo iria trabalhar somente com pulsares hehe. O que mais me instigou foi a aplicação das técnicas passadas a astrofísica, o seu embasamento e suas limitações. Foi um apanhado geral e pode ser considerado como introdutório.

Finalmente sei por onde continuar porque ter começado aqui foi um acerto e tanto!

por Adnan R

14 de jul. de 2020

An excellent introduction to the use of software in handling the vast quantities of data generated in astronomy. It isn't possible for a course intended to take a few hours per week to cover things in great depth.

Some interesting astronomy is covered. There are astronomy quizzes but not much physics / astronomy knowledge is necessary.

This is mainly a programming course. The 1hr estimate for Python exercises is optimistic especially for students who have little programming experience. Ideally, students should have done an introductory Python course. The importance of software performance when handling large amounts of data is emphasised.

The course also covers SQL - a useful skill, but no background necessary IMO.

The final two weeks cover machine learning applied to astronomy: how it can be useful, some pitfalls, and checking the machine learning model's quality.

por Jonathan C

29 de dic. de 2017

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.

por Javier E

10 de oct. de 2019

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.

por Arnaud D

18 de ago. de 2018

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.

por Arunav R

10 de jun. de 2020

This course was such a big help to me . I leaned about astronomy as well as develop some skills of data science which might help me in other platforms as well. The explanation was good and I liked all the real time problems .

One thing is that providing the solutions of the code makes it easy for us to solve the coding problems and it's very intimidating to look at the solution if we're stuck somewhere in the coding. It's a kind of a downside when viewed in a neutral perspective .

Other than that the content was really good and hopefully advanced courses of this course will be provided to us.

Cheers . Thank you!

por Amrit N

10 de ago. de 2020

This course is absolutely for beginners. Very minimal knowledge of python is required. The course is perfectly designed for beginners. The contents are present in so lucid manner and the instruction to complete the activities are so easy to follow. If you are interested in learning python a bit and as well apply them to build concepts of astronomy, the boom, you are at the right place! Go ahead and get yourself some pretty pictures of the universe or be happy with how you make the first machine learning regression/classification of galaxies. Whatever pleases you!

por Santiago M Z O

8 de sep. de 2018

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.

por Harshal G H

14 de jun. de 2018

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.