Informações sobre o curso
4.9
236 ratings
75 reviews
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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Intermediate Level

Nível intermediário

Clock

Sugerido: 6 weeks of study, 4-6 hours/week

Aprox. 19 horas restantes
Comment Dots

English

Legendas: English

Habilidades que você terá

Python ProgrammingMachine LearningSqlApplied Machine Learning
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Sugerido: 6 weeks of study, 4-6 hours/week

Aprox. 19 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
4 horas para concluir

Thinking about data

This module introduces the idea of computational thinking, and how big data can make simple problems quite challenging to solve. We use the example of calculating the median and mean stack of a set of radio astronomy images to illustrate some of the issues you encounter when working with large datasets. ...
Reading
8 vídeos (Total de 30 min), 1 leitura, 4 testes
Video8 videos
Course overview2min
Pulsars3min
Diving in: imaging stacking5min
Challenge: the median doesn't scale2min
The solution: improving your method3min
Module summary1min
Interview with Aris Karastergiou6min
Reading1 leituras
Further reading10min
Quiz1 exercício prático
Pulsars: test your understanding10min

2

Seção
Clock
4 horas para concluir

Big data makes things slow

In this module we explore the idea of scaling your code. Some algorithms scale well as your dataset increases, but others become impossibly slow. We look at some of the reason for this, and use the example of cross-matching astronomical catalogues to demonstrate what kind of improvements you can make. ...
Reading
7 vídeos (Total de 35 min), 3 testes
Video7 videos
Supermassive black holes3min
What is cross-matching?4min
Evaluating time complexity5min
A (much) faster algorithm6min
Module summary2min
Interview with Brendon Brewer8min
Quiz1 exercício prático
Supermassive black holes: test your understanding10min

3

Seção
Clock
4 horas para concluir

Querying your data

Most large astronomy projects use databases to manage their data. In this module we introduce SQL - the language most commonly used to query databases. We use SQL to query the NASA Exoplanet database and investigate the habitability of planets in other solar systems....
Reading
7 vídeos (Total de 35 min), 3 testes
Video7 videos
Exoplanets4min
Querying database with SQL4min
More advanced SQL4min
Joining tables in SQL6min
Module summary2min
Interview with Jon Jenkins8min
Quiz1 exercício prático
Exoplanets - test your understanding10min

4

Seção
Clock
4 horas para concluir

Managing your data

This module introduces the basic principles of setting up databases. We look at how to set up new tables, and then how to combine Python and SQL to get the best out of both approaches. We use these tools to explore the life of stars in a stellar cluster. ...
Reading
6 vídeos (Total de 29 min), 3 testes
Video6 videos
The lifecycle of stars6min
Setting up your own database5min
Exploring a star cluster4min
Module summary2min
Interview with Emily Petroff6min
Quiz1 exercício prático
Stars - test your understanding10min
4.9
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17%

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Briefcase

83%

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Melhores avaliações

por GMJun 30th 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.

por JMJul 15th 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!

Instrutores

Tara Murphy

Associate Professor
School of Physics

Simon Murphy

Postdoctoral Researcher
School of Physics

Sobre The University of Sydney

The University of Sydney is one of the world’s leading comprehensive research and teaching universities, consistently ranked in the top 1 percent of universities in the world. In 2015, we were ranked 45 in the QS World University Rankings, and 100 percent of our research was rated at above, or well above, world standard in the Excellence in Research for Australia report....

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • We assume you are familiar with basic programming in a modern programming language including variables, control structures, data structures, functions, and working with files. In this course we will use Python 3.

    We'll walk through all the examples and provide lots of support, so jump in and have a go. If haven't done any programming for a while, you might want to brush up before you start.

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