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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 re...
(1,047 reviews)
23,826 students
Created by


CourseMarks Score®







Platform: Coursera
Video: 3h 31m
Language: English

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Detailed Analysis

CourseMarks Score®

9.1 / 10

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Freshness Score

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.9 / 10
We analyzed factors such as the rating (4.8/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

8.8 / 10
Video Score: 8.1 / 10
The course includes 3h 31m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
Detail Score: 8.4 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.8 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

2 articles.
0 resource.
0 exercise.
6 tests or quizzes.

Table of contents


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.

You will learn


Basic knowledge of Physics and Astronomy is required to start this course, as this is an intermediate level course.

This course is for

This course was made for intermediate-level students.

How much does the Data-driven Astronomy course cost? Is it worth it?

Access to most course materials is FREE in audit mode on Coursera. If you wish to earn a certificate and access graded assignments, you must purchase the certificate experience during or after your audit.

If the course does not offer the audit option, you can still take a free 7-day trial.

Does the Data-driven Astronomy course have a money back guarantee or refund policy?

Coursera offers a 7-day free trial for subscribers.

Are there any SCHOLARSHIPS for this course?

YES, you can get a scholarship or Financial Aid for Coursera courses. The first step is to fill out an application about your educational background, career goals, and financial circumstances. Learn more about financial aid on Coursera.

Who is the instructor? Is Tara Murphy a SCAM or a TRUSTED instructor?

Tara Murphy has created 1 courses that got 282 reviews which are generally positive. Tara Murphy has taught 23826 students and received a 4.8 average review out of 282 reviews. Depending on the information available, Tara Murphy is a TRUSTED instructor.
School of Physics
University of Sydney
Tara Murphy is an astrophysicist working in the School of Physics at the University of Sydney. She is a Australian Research Council Future Fellow and a Chief Investigator in the ARC Centre of Excellence for All Sky Astrophysics. Her research focuses on detecting and studying transient and highly variable astrophysical phenomena with next generation radio telescopes. In particular, she is interested in developing and applying novel computer science techniques to data-intensive research. She leads an international team of researchers searching for variable and transient sources with the Murchison Widefield Array and the Australian SKA Pathfinder telescopes in Western Australia. Tara is also passionate about teaching and high school outreach. She has been a director of the National Computer Science School since 2004 and director of the NCSS Challenge, an online programming competition that has taught thousands of high school students how to code. In 2012 her work in scientific research and public outreach was recognised by the award of NSW Young Tall Poppy of the year and she also received an ALTC Citation for Outstanding Contribution to Student Learning in 2010.


CourseMarks Score®







Platform: Coursera
Video: 3h 31m
Language: English

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