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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

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The University of Sydney

Rating 4.8 based on 104 ratings
Length 7 weeks
Effort 6 weeks of study, 4-6 hours/week
Starts May 6 (3 weeks ago)
Cost $49
From The University of Sydney via Coursera
Instructors Tara Murphy, Simon Murphy
Download Videos On all desktop and mobile devices
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 18 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 8 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.

Highly recommended!

Highly recommend it anyone curious about Universe and to understand it better!

Overall the course is great, I highly recommend it to astronomers who want to learn some new tricks in data science.

For anyone intrested in Astrostats & Astroinformatics, highly recommended!

data analysis in 6 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.

Really good basic intro to data analysis, particularly applying this to the astronomical domain.

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.

even though in 4 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.

My only concern is that I would love to have some form of a certificate even though I can not afford to pay for the course.

curious about in 4 reviews

Being a physics student by formal education and a star gazer too, I am familiar with the theory but was always curious about how to they measure distances, how do they measure red-shifts etc when the distant galaxies are themselves so faint.

big data in 4 reviews

Good introduction course to big data.

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

Thank you :) Pretty good introduction to both Big Data treatment and modern astronomy!

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Coursera

&

The University of Sydney

Rating 4.8 based on 104 ratings
Length 7 weeks
Effort 6 weeks of study, 4-6 hours/week
Starts May 6 (3 weeks ago)
Cost $49
From The University of Sydney via Coursera
Instructors Tara Murphy, Simon Murphy
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Engineering Science
Tags Data Science Data Analysis Physical Science And Engineering Physics And Astronomy

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