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Data-driven Astronomy

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.

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Coursera

&

The University of Sydney

Rating 4.8 based on 65 ratings
Length 7 weeks
Effort 6 weeks of study, 4-6 hours/week
Starts Jun 4 (29 weeks ago)
Cost $49
From The University of Sydney via Coursera
Instructors Tara Murphy, Simon Murphy
Free Limited Content
Language English
Subjects Data Science Engineering Science
Tags Data Science Data Analysis Physical Science And Engineering Physics And Astronomy

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

machine learning in 11 reviews

A great course for a good understanding of the tools and the theoretical requisites of data driven astronomy Great course to get an overview of the type of problems that astronomy faces and how to use data and machine learning techniques to solve them.

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.

A solid, compact, no-nonsense introduction to machine learning in Astronomy using Python's rich scientific tool sets.

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.

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.

That was the course I was looking for, after taking a course on Machine Learning by Andrea NG, from Stanford University.

I learned a lot about astronomy, quasars, galaxies, machine learning, python and the scientific libraries numpy, scikit-learn, scipy, creating programs that are optimised in memory use and that complete in reasonable time Unique course, very much excited to learn new things 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.

highly recommend in 4 reviews

Highly recommended course for both astronomical and computer science students.

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

=) I highly recommend this course if you are curious about some of the big data tools and techniques used in astronomy.

I highly recommend it.

data analysis in 4 reviews

The teachers use a wide range of astronomical subjects to illustrate the different techniques used in data analysis.

I would recommend it to everyone interested in data analysis in modern science.

A great course that helps one understand the basics of data analysis and how they are used in observational astronomy.

What a perfect blend of real astronomy, programming, Python, SQL, machine-learning, and data analysis.

even though in 3 reviews

Learned a great deal even though I'm not an astronomer.

I've never enjoyed using a Programming language to solve, even though at a beginner's level, problems up until this class.

A very interesting course, even though I am not an astronomer.

real world in 3 reviews

Don't expect to to be able to solve problems on the scale of the real world, er... universe with the obtained knowledge.

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.

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.

big data in 3 reviews

Good introduction course to big data.

Course follows a very intuitive approach to impart modern astronomy knowledge with big data as a backdrop.

Careers

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Coursera

&

The University of Sydney

Rating 4.8 based on 65 ratings
Length 7 weeks
Effort 6 weeks of study, 4-6 hours/week
Starts Jun 4 (29 weeks ago)
Cost $49
From The University of Sydney via Coursera
Instructors Tara Murphy, Simon Murphy
Free Limited Content
Language English
Subjects Data Science Engineering Science
Tags Data Science Data Analysis Physical Science And Engineering Physics And Astronomy