The University of Sydney - Data-driven Astronomy
- Offered byCoursera
Data-driven Astronomy at Coursera Overview
Duration | 23 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course |
Credential | Certificate |
Data-driven Astronomy at Coursera Highlights
- Earn a certificate after completion of the course
- Financial aid facility available
- Projects and assignments for better preparation
Data-driven Astronomy at Coursera Course details
Undergraduate and Graduate Students in Astronomy and Astrophysics
Data Scientists and Analysts
Professional Astronomers and Astrophysicists
Understand the key challenges and opportunities in data-driven astronomy
Apply data science techniques to analyze and interpret astronomical data
Use computational tools to manage and visualize large datasets
Develop machine learning models for specific astronomical applications
Critically evaluate the ethical implications of data usage in astronomy
The course aims to equip students with the skills to analyze, interpret, and draw meaningful insights from large and complex datasets that are common in modern astronomy
This course introduces students to the principles and practices of data science within the context of astronomy
Students will learn to harness the power of large astronomical datasets to explore the universe and answer fundamental questions about its origin, structure, and evolution
Data-driven Astronomy at Coursera Curriculum
Thinking about data
Thinking about data
Course overview
Pulsars
Diving in: imaging stacking
Challenge: the median doesn't scale
The solution: improving your method
Module summary
Interview with Aris Karastergiou
Further reading
Pulsars: test your understanding
Big data makes things slow
Big data makes things slow
Supermassive black holes
What is cross-matching?
Evaluating time complexity
A (much) faster algorithm
Module summary
Interview with Brendon Brewer
Supermassive black holes: test your understanding
Querying your data
Organising your data
Exoplanets
Querying database with SQL
More advanced SQL
Joining tables in SQL
Module summary
Interview with Jon Jenkins
Exoplanets - test your understanding
Managing your data
Managing your big datasets
The lifecycle of stars
Setting up your own database
Exploring a star cluster
Module summary
Interview with Emily Petroff
Stars - test your understanding
Learning from data: regression
Learning from data
The cosmological distance scale
What is machine learning?
Decision tree classifiers
Estimating redshifts using regression
Summary
Interview with Ashish Mahabal
Cosmological distances - test your understanding
Learning from data: classification
Classifying your data
Types of galaxies
Morphological classification of galaxies
Limitations of decision tree classifiers
Improving our results with ensemble classifiers
Module summary
Interview with Karen Masters
Classify some galaxies by hand!
Galaxies - test your understanding