Compare courses
Register
Crawford School of Public Policy

Big Data in the Public Sector

Sep 18, 2019
Canberra, Australia
AUD 1195 ≈USD 807
AUD 1195 per day

How it works

Disclaimer

Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with Crawford School of Public Policy.

Full disclaimer.

Description

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

The course will provide an overview of relevant machine learning tools, explain the intuition behind these tools, illustrate their application using the publicly available software package Python, and explain how to interpret and compare competing machine learning systems (such as Lasso, Ridge, Elastic Net, Trees, Random Forests, Boosting, Stacking). The course will conclude with a guided group discussion of the risks and opportunities associated with the application of machine learning algorithms.

The course will provide participants with the knowledge they require to understand the intuition behind relevant machine learning algorithms. Students will learn how to get started using the publicly available software package Python to analyse big data. The course will combine intuitive explanations with practical examples. The course is suitable for beginners.

Experts

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...

Next dates

Sep 18, 2019
Canberra, Australia
AUD 1195 ≈USD 807
AUD 1195 per day

How it works

Show more