Programme Overview:
- Duration:
- 1 Years / 18 Months
- Attendance:
- Full Time / Part Time
- Mode of Delivery:
- Face-to-Face
- Next Intake:
- 2023/2024 September
- Contact Name:
- Spire Graduate
- Contact Number:
- Please click 'Ask a Question'
- Fees:
- Fee Information
The explosion of online and social media, the proliferation of digitized information, and improved electronic access to political decision-making processes provide new opportunities to study existing and emerging political processes in various democratic and non-democratic political regimes. The simultaneous development of cutting-edge data science methods to study digital text, audio, and video provide the tools we need to take advantage of these opportunities. The GradDipPolitics and Data Science is designed to equip students with the theoretical knowledge and methodological skills necessary to examine and understand politics in the digital age.
The GradDipPolitics and Data Science programme is organised around two streams of study. The first stream grounds students with backgrounds in political science and related social sciences in data science methods. The second stream is geared towards students with computer science or related technical backgrounds, teaching them about research design and theories in political science.
Apart from the three core modules in the Social Science Background stream, students can select three modules that best fit their interest. Apart from the core module and the core optional module in the Technical Background stream, students select four modules that best fit their interest. These modules can either revolve around methods needed to study digital and digitised politics, such as programming and machine learning, quantitative text analysis, statistics, and experimental methods. Or they can be modules relating to comparative politics, international relations, political violence, political economy, and related fields that the School of Politics and International Relations has strengths in.
The programme thus provides a thorough grounding in political science and its sub-disciplines, and in-depth training in the empirical methods necessary to study important questions emerging in these areas of study. It is specifically aimed towards students who want a cutting-edge training in politics and data science but who are less interested in writing a master’s thesis.
Graduates from this programme will be ideally equipped for careers in a large and varied set of employment sectors. The combination of a solid understanding of social science theory and the technical ability to apply advanced data-science approaches to answer questions of political and societal relevance, makes our graduates a unique addition to any data science team.
Potential future employers include:
Potential roles include
Curricular information is subject to change
Full Time option suitable for:
Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. Yes
Part Time option suitable for:
Domestic(EEA) applicants: Yes
International (Non EEA) applicants currently residing outside of the EEA Region. No
The GradDip in Politics and Data Science is aimed towards students with backgrounds in political science and related social sciences with a strong interest in learning data science methods, and towards students with a Computer Science or related technical background who want to study politics. It is specifically aimed towards students who want a cutting-edge training in politics and data science but who are less interested in writing a master’s thesis.
The programme shall equip students with both the theoretical overview and the empirical tools necessary to understand and engage with the brave new world of digitised politics, and the expansion in scale, types, and complexity of data available to study political phenomenon. The MSc in Politics and Data Science provides students with in-depth knowledge of political science theories and approaches and the methodological training to apply these tools in a theoretically-informed manner. It offers advanced training in statistical and computational methods, including tools to extract and prepare unstructured data (data wrangling), to detect patterns and predict behaviour based on statistical data, to evaluate the veracity of theoretical models on large-scale datasets, to analyse highly interconnected data from networks and spatial data sets, and to develop simulations to evaluate the inherent consistency and implications of theoretical arguments.
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.
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
Applying knowledge and understanding
Making judgements
Communications and working skills
Learning skills
The GradDip Politics and Data Science programme is organised around two streams of study. The first stream grounds students with backgrounds in political science and related social sciences in data science methods. The second stream is geared towards students with computer science or related technical backgrounds, teaching them about research design and theories in political science. Apart from two required core modules in each stream, all students can select four optional modules that best fit their interests. These modules can either revolve around methods needed to study digital and digitised politics, such as programming and machine learning, quantitative text analysis, statistics, and experimental methods. Or they can be modules relating to comparative politics, international relations, political violence, political economy, and related fields that the School of Politics and International Relations has strengths in.
The Graduate Diploma in Politics and Data Science is a 60-credit programme.
Full time students must take three 10-credit modules in the first trimester and three 10-credit modules in the second trimester.
Depending on their performance, aspirations and selection of modules, students may be able to transfer from the graduate diploma into the MSc Politics and Data Science after the first trimester.
Core and Option Modules for MSc Politics and Data Science Social Science Background Stream
These are the current modules for 2023/24 but are subject to change. Each of the following modules carries 10 credits unless otherwise specified.
Core Modules
Core Option Modules - Select one
Option Modules
Autumn
Spring
Core and Option Modules for MSc Politics and Data Science Technical Background Stream
These are the current modules for 2023/24 but are subject to change. Each of the following modules carries 10 credits unless otherwise specified.
Core Modules
Core Option Modules - Select one
Option Modules
Autumn
Spring
GradDip Politics & Data Science (W475) Full Time
EU fee per year - € 7440
nonEU fee per year - € 14350
GradDip Politics & Data Science (W476) Part Time
EU fee per year - € 4920
nonEU fee per year - € 7180
***Fees are subject to change
Tuition fee information is available on the UCD Fees website. Please note that UCD offers a number of graduate scholarships for full-time, self-funding international students, holding an offer of a place on a UCD graduate degree programme. For further information please see International Scholarships.
Good undergraduate degree (2.1 or equivalent, or 2.2 or equivalent with relevant work experience) in political science or related social science, or in computer science, statistics, or related discipline. Because of the streaming of the module structure of the program, we can accommodate students with a social science as well as students with a more technical background.