Who is this class for: This course is aimed at science students with an interest in computational approaches to problem solving, people with an interest in astronomy who would like to learn current research methods, or people who would like to improve their programming by applying it to astronomy examples.

Created by:  The University of Sydney

  • Tara Murphy

    Taught by:  Tara Murphy, Associate Professor

    School of Physics

  • Simon Murphy

    Taught by:  Simon Murphy, Postdoctoral Researcher

    School of Physics
Commitment6 weeks of study, 4-6 hours/week
Hardware ReqYou'll need to have a computer with internet access.
How To PassPass all graded assignments to complete the course.
User Ratings
4.8 stars
Average User Rating 4.8See what learners said

How It Works

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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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.
Ratings and Reviews
Rated 4.8 out of 5 of 14 ratings

A great course you may study if you are interested in Astronomy and Python!

This course lies in the confluence of both my professional experience (software development in the IT industry) and the science that interests me the most: astronomy and astrophysics. Just a glance at the syllabus was enough to convince me that the course would be worth taking, due to its good structure and wide scope, covering current trends in both data science and computational astronomy.

From previous online course experience in these areas, I knew at the beginning that contents can be hard to grasp if the theory and practice are not well balanced, but it turned out to be a great run, with enough depth to pique one's interest while at the same time feeling comfortable using both past and newly acquired knowledge.

The course sports an excellent tool to solve and test the programming assignments that constitute most of the grades you will earn. Thanks to it, you will be freed, as a student, from the most common hassles in online courses involving coding (mainly environment setup). Which means more chances to focus on the main subjects covered and a pleasant wading through the challenges posed.

Beware that if you are already comfortable ín the programming language used (Python), you may easily be craving for more advanced assignments, but this I'm sure is easy to request from the helpful professors and staff. If you are instead a novice with regards to coding, additional parallel effort may be required, but the course contents will guide you well in the endeavor.

One aspect of the course that may be specially challenging is the relatively speedy run through the theory and concepts of Machine Learning. 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. I would expect that if you have not had previous contact with the subject, the contents can feel a bit daunting. But with some extra commitment (check the numerous online resources, take a parallel course...) I am pretty sure this can be overcome.

Great class! I didn't know that these techniques were used in astronomy. I am looking forward to more science and scientific computing courses from Coursera.

Excellent course for astronomy enthusiasts with really useful and informative Python Assignments. One of the best MOOCs I have attended.