The key objective is to have graduates who are able to join data science teams in the Government, corporate, or private sectors, with sufficient understanding of technical concepts in data science and machine learning to collaborate with computer scientists and engineers and with sufficient understanding of social science and politics to be able to bring a deeper understanding of human behaviour to otherwise technology oriented teams.
Core modules for the Social Science Background stream provide a foundational understanding of data science methods, while optional modules allow exploration into specialised areas like machine learning, quantitative text analysis, and the ethical use of AI in politics. Similarly, the Technical Background stream includes core and elective modules that blend technical skills with an understanding of political science theories and applications.
Graduates can also use the skills acquired to continue work in political science research, either in academia, think tanks, or the non-profit or public sector, where they will benefit from a deep understanding of the cross-section between data science and political science.
Knowledge and understanding
- Understanding the range of data science and machine learning methodologies that are available to data scientists, and their key advantages and disadvantages.
- Understanding of theories of political behaviour, political processes, and political institutions.
- Understanding variations in political systems and their functioning.
Applying knowledge and understanding
- Understanding of central aspects of political and social science research design, such as conceptualization, operationalization and measurement.
- Ability to use knowledge of research design to systematically address questions pertaining politics and public policy.
- Gain general experience in applying data science techniques to questions of political and social science relevance.
Making judgements
- Ability to decide on appropriate statistical techniques given a particular research question in relation to political behaviour and public policy.
- Ability to evaluate reported statistical and algorithmic results in political and social science research.
- Through training in general research design, ability to evaluate the veracity of input data of political and social behaviour for use in data science applications.
- Have a basic understanding of the situations where automated techniques as used in standard data science practice are suitable and ethically appropriate, and where not.
Communications and working skills
- Ability to clearly communicate results from statistical analysis of political and social behaviour.
- Ability to communicate the possibilities and scope of data science tools for the understanding of political and social behaviour.
- Basic practice in team work and learning how to collaborate in larger technical projects, including ability to work with techniques for code sharing, agile development, tools for scientific replication, etcetera.
Learning skills
- Have sufficient grounding in fundamentals of statistical analysis and computer science to be able to acquire new skills in data science.
- Have sufficient grounding in political and social science to be able to read into new domains of political and social science research.