Big Data in the Public Sector

Crawford School of Public Policy

Crawford School of Public Policy

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Who should attend

This course is recommended for APS staff and is relevant to all departments. No prior experience or knowledge is required.

About the course

The possibility of using big data in combination with machine learning algorithms creates a range of challenges and opportunities for policymakers. Understanding these is not only essential for the responsible application of machine learning tools to administrative records but also for the design of appropriate data protection laws and – where necessary – the informed regulation of private sector activity.

This course will develop your skills to understand the intuition behind relevant machine learning tools, provide examples for how to apply these tools using the software package Python, and explain how to interpret and compare competing machine learning systems. The course will conclude with a discussion of the risks and opportunities associated with the application of machine learning algorithms.

Course overview

The possibility of using big data in combination with machine learning algorithms creates a range of challenges and opportunities for policymakers. Understanding these challenges and opportunities is not only essential for the responsible application of machine learning tools to administrative records but also for the design of appropriate data protection laws and - where necessary - the informed regulation of private sector activity.

The course will cover four main topics:

  • Introduction and overview
  • Applications and examples
  • Model competition
  • Guided group discussion of challenges and opportunities

Learning outcomes

This course will provide participants with the knowledge they require to understand the intuition behind relevant machine learning algorithms. Participants will learn how to get started using a publicly available software package to analyse big data.

  • get an overview of relevant machine learning tools
  • illustrate application of the tools using the publicly available software package; Python.
  • interpret and compare competing machine learning systems

This course will include a guided group discussion of the risks and opportunities associated with the application of machine learning algorithms.

Experts

Mathias Sinning

Mathias Sinning is the Deputy Director of the ANU Tax and Transfer Policy Institute. He has previously held academic appointments at the ANU and the University of Queensland and has been a Visiting Fellow at Princeton University. Mathias is interested in the empirical analysis of issues related t...

Big Data in the Public Sector at Crawford School of Public Policy

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Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.

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