GradDip Politics & Data Science

Graduate Taught (level 9 nfq, credits 60)

The Graduate Diploma Politics and Data Science programme is specifically tailored to address the transformative impact of generative AI, large language models, and machine learning on political processes and their ethical implications. This cutting-edge degree is an ideal choice for applicants from diverse backgrounds, aiming to explore the intersection of politics and advanced data science in the digital era.

The curriculum delves deeply into the ways generative AI and large language models are revolutionising our understanding of political discourse, public opinion, and policy-making. With a focus on the ethical and societal implications of these technologies, the programme equips students with a critical perspective on how data science shapes political narratives and decisions in both democratic and non-democratic regimes.

Structured in two streams, the programme caters to students from varying academic backgrounds. The first stream introduces students from social sciences, including political science, to advanced data science methods, emphasising the use of large language models and machine learning in political analysis. The second stream, tailored for those with a technical background, focuses on political science research design and theories, integrating these with data science applications.

This programme not only offers comprehensive training in political science and its sub-disciplines but also equips students with empirical skills to navigate and analyse the complex interplay between politics and technology in the modern world. It prepares graduates to critically assess and contribute to the evolving landscape of politics in the age of data science and AI.

Careers & Employability

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 cutting-edge data-science and AI approaches to answer questions of political and societal relevance, makes our graduates a unique addition to any data science team. Furthermore, graduates will be well-positioned to apply for quantitative social science PhD programmes with the aim of pursuing an academic career.

Potential future employers include:

  • Government
  • Tech industry
  • Corporate Sector
  • International Organisations (EU, UN, WTO, World Bank)
  • Non-Government Organisations
  • Not-for-profit sector
  • Public opinion institutes
  • Think tanks

Potential roles include

  • Political Advisor
  • Social Data Specialist
  • Data Scientist
  • Chief Information Officer
  • Social Science PhD candidate

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.

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.

Featured Modules

The GradDip Politics and Data Science consists of a variety of modules designed to train learners to become experts in the latest quantitative methodologies and research skills. Below, we describe a selection of modules students can choose from. The full list of modules is available below under ”Which modules can I take?”

Introduction to Statistics: This module offers an overview of statistical analysis fundamentals in political science and related fields, focusing on measurement, variables, and statistical data handling. It introduces descriptive statistics, multiple regression analysis, and statistical inference, teaching students to draw conclusions from sample data. The course also covers practical R programming for data analysis, addressing linear regression assumptions, estimation, and inference. Key topics include data visualization, regression models, hypothesis testing, and logistic regression. Upon completion, students will understand basic statistical concepts, R programming, and be able to interpret regression analyses, equipping them for analytical tasks in social science research.

Quantitative Text Analysis: Quantitative Text Analysis equips students with the ability to analyse vast text corpora, employing both traditional statistical methods and cutting-edge machine learning techniques like transformer models and Large Language Models. Throughout this module, students will gain hands-on experience in the R and Python programming languages, learning to navigate the process from data extraction to analysis. The module combines established text-as-data methods and advanced methods, including transformer-based machine learning, word embeddings, and Large Language Models,  preparing students to apply these methods to address important social and political questions. By mastering these skills, students are set to harness the full potential of automated text analysis in their future careers.

Programming for Social Scientists: This module serves as a foundational course in computer programming, focusing on Python, currently the third most popular programming language and a favourite among data scientists for its accessibility and versatility. It is designed to equip students, particularly those in the social sciences, with the skills to automate tasks and develop more complex software, in particular using object-oriented design patterns.  The curriculum emphasises hands-on learning through the development of a social simulation project in teams, allowing students to apply basic programming skills to a range of applications including file manipulation, user interface design, simulation modelling, and result visualisation. Combining lectures with labs and homeworks, the module supports practice with Python and related tools, fostering collaboration and self-reflection. 

Politics of (Mis)Information: This module delves into the impact of information and misinformation. It investigates how information is produced, disseminated, and influences individuals, organizations, and political institutions. The course examines the effects of political information availability on decision-making and policy outcomes. Students will emerge with a deeper understanding of the information’s role in society. Learning outcomes include analyzing misinformation’s impact on political decisions, understanding the evolving information environment, applying theories on misinformation in politics, articulating key information politics concepts, and addressing society’s challenges from an evidence-based viewpoint.

Connected Politics: Under the guidance of both a project and a module coordinator, small teams will tackle a pressing social or political question using advanced methodologies such as quantitative text analysis, machine learning, image recognition, and network analysis. The focus is on developing teamwork skills, setting and achieving goals, and effectively distributing tasks within the group. Throughout the module, students will learn vital aspects of research design, substantive theory, formulating research questions, case-selection strategies, and the importance of open science practices. They will also explore the concepts of replicability and reproducibility in research. The results of projects from previous years have appeared in peer-reviewed journals, and groups have also presented their work at professional conferences such as the Annual Conference of the American Political Science Association.

AI and Language Models in Politics: This module on AI and language models (LMs) equips students with an in-depth understanding of cutting-edge language models’ theoretical foundations, development techniques, ethical considerations, and practical applications. The module aims to provide students with the knowledge and skills necessary to design, implement, and evaluate language models in political contexts, and to critically analyse the implications of deploying such models. Throughout the course, students will explore topics including the architecture of neural networks underlying LMs, the effects of data collection and processing methods, model training and fine-tuning processes, and the evaluation of model performance and bias. Ethical considerations will be woven throughout the curriculum, addressing issues such as privacy, bias, fairness, and the societal impact of automated language generation. Students to gain hands-on experience with LMs, preparing them for research, development, and policy-making roles where AI and language technologies are due to play an increasing role.

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 cutting-edge data-science and AI approaches to answer questions of political and societal relevance, makes our graduates a unique addition to any data science team. Furthermore, graduates will be well-positioned to apply for quantitative social science PhD programmes with the aim of pursuing an academic career.

Potential future employers include:

  • Government
  • Tech industry
  • Corporate Sector
  • International Organisations (EU, UN, WTO, World Bank)
  • Non-Government Organisations
  • Not-for-profit sector
  • Public opinion institutes
  • Think tanks

Potential roles include

  • Political Advisor
  • Social Data Specialist
  • Data Scientist
  • Chief Information Officer
  • Social Science PhD candidate

View All Modules Here

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. See this page for more details.

Core and Option Modules for MSc Politics and Data Science Social Science Background Stream 

These are the current modules for 2024/25 but are subject to change. Each of the following modules carries 10 credits unless otherwise specified. 

Core Modules

  • POL40950 Introduction to Statistics (Autumn)
  • POL42340 Programming for Social Scientists (Spring) 
  • POL42350 Connected_Politics (Spring) 
  • POL42540 Applied Data Wrangling and Visualisation (Autumn) (5-Credits) (NEW)
  • POL42570 Connected_Politics 1 (Autumn) (5-Credits) (NEW)

Core Option Modules - Select one

  • POL42560 AI and Large Language Models (NEW) (Spring) 
  • POL42050 Quantitative Text Analysis (Spring) 
  • SOC41070 Sociological Thinking in the Digital Age (Spring) ​

Option Modules

Autumn

  • IS40840 Data & Society
  • POL40050 Theories of International Relations
  • POL40140 Theories of Global Justice
  • POL40160 Comparative Public Policy
  • POL40540 Comparative European Politics
  • POL41020 Politics of Human Rights
  • POL41510 Politics and Change in the Middle East and North Africa
  • POL41980 Peace & Conflict Studies
  • POL42040 Gender & the Political System
  • POL42070 Politics of (mis-)information
  • POL42530 The Politics of International Trade and Investment (NEW)
  • POL42550 Feminist Theory (NEW)
  • SOC41130 AI and Society

Spring

  • DEV40020 Gender and Development
  • POL40100 Politics of Development
  • POL40370 International Political Economy
  • POL40610 EU Foreign, Security, and Defence Policy
  • POL40970 Politics of European Governance
  • POL41030 Theory of Human Rights
  • POL41640 Qualitative Research Methods for Political Science
  • POL41720 Gender Peace and Security
  • POL41860 Governance, Politics and Development
  • POL41910 Political Violence (NEW)
  • POL42050 Quantitative Text Analysis
  • POL42060 International Security
  • POL42430 IR Theory: Conflict and Identity (NEW)
  • POL42500 Politics of Authoritarianism
  • SOC41070 Sociological Thinking in the Digital Age

Core and Option Modules for MSc Politics and Data Science Technical Background Stream 

These are the current modules for 2024/25 but are subject to change. Each of the following modules carries 10 credits unless otherwise specified. 

Core Modules

  • POL42350 Connected_Politics (Spring) 
  • POL42070 Politics of (mis-)information (Autumn)
  • POL42540 Applied Data Wrangling and Visualisation (Autumn) (5-Credits) (NEW)
  • POL42570 Connected_Politics 1 (Autumn) (5-Credits) (NEW)

Core Option Modules - Select one

  • POL42560 AI and Large Language Models (NEW) (Spring) 
  • POL42050 Quantitative Text Analysis (Spring) 
  • POL42340 Programming for Social Scientists (Spring)
  • SOC41070 Sociological Thinking in the Digital Age (Spring) ​

Option Modules

Autumn

  • IS40840 Data & Society
  • POL40050 Theories of International Relations
  • POL40140 Theories of Global Justice
  • POL40160 Comparative Public Policy
  • POL40540 Comparative European Politics
  • POL40950 Introduction to Statistics
  • POL41020 Politics of Human Rights
  • POL41510 Politics and Change in the Middle East and North Africa
  • POL41980 Peace & Conflict Studies
  • POL42040 Gender & the Political System
  • POL42530 The Politics of International Trade and Investment (NEW)
  • POL42550 Feminist Theory (NEW)
  • SOC41130 AI and Society

Spring

  • DEV40020 Gender and Development
  • POL40100 Politics of Development
  • POL40370 International Political Economy
  • POL40610 EU Foreign, Security, and Defence Policy
  • POL40970 Politics of European Governance
  • POL41030 Theory of Human Rights
  • POL41640 Qualitative Research Methods for Political Science
  • POL41720 Gender Peace and Security
  • POL41860 Governance, Politics and Development
  • POL41910 Political Violence (NEW)
  • POL42050 Quantitative Text Analysis
  • POL42060 International Security
  • POL42340 Programming for Social Scientists
  • POL42430 IR Theory: Conflict and Identity (NEW)
  • POL42500 Politics of Authoritarianism
  • SOC41070 Sociological Thinking in the Digital Age

Graduate Diploma Politics & Data Science (W475) Full Time
EU          fee per year - € 7810
nonEU    fee per year - € 15070

Graduate Diploma Politics & Data Science (W476) Part Time
EU          fee per year - € 5170
nonEU    fee per year - € 7540

***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.

  • Your application will be considered on its individual merits and relevant professional experience will also be taken into account.
  • English language requirements: applicants whose first language is not English should have met TOEFL, IELTs, or computer-based TOEFL requirements (600, 6.5, or 250 respectively), or the Cambridge English Test (Certificate in Advanced English at a minimum of Grade B, or Certificate of Proficiency in English at Grade C). Applicants who obtained a previous degree from an English-speaking university may be exempted from this requirement. Click here for further info.
  • These are the minimum entry requirements – additional criteria may be requested for some programmes

The following entry routes are available:

GD Politics & Data Science FT (W475)
Duration
1 Years
Attend
Full Time
Deadline
Rolling*
GD Politics & Data Science PT (W476)
Duration
18 Months
Attend
Part Time
Deadline
Rolling*

* Courses will remain open until such time as all places have been filled, therefore early application is advised

A comphrensive FAQ can be found here