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MSc in Politics and Data Science
The MSc 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 course 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, emphasizing 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.
One appealing aspect of our MSc Politics and Data Science is that modules that involve programming skills are taught by social scientists, ensuring lecturers share a common background with students. This approach fosters better understanding and ensures technical modules are relevant to political and social contexts, enhancing the learning experience.
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.
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.
Featured Modules
The MSc 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 have the opportunity to chose from. Please note that these are selected example modules and some are not guaranteed to run each year.
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 visualisation, regression models, hypothesis testing, and logistic regression. Upon completion, students will understand basic statistical concepts and R programming and be able to interpret regression analyses, equipping them for analytical tasks in social science research.
Applied Data Wrangling and Visualisation: This module provides a practical introduction to data management and visualisation techniques using R. Students will learn essential skills in data cleaning, wrangling, merging, and handling various file formats. The course also introduces AI tools for coding assistance, project management, and automation in data workflows. Beyond data preparation, the module covers the principles of effective data visualisation, guiding students through applied techniques for creating clear and engaging visual representations of data. It also includes an introduction to relational databases with SQL and web scraping for data collection, enabling students to work with large datasets efficiently. By the end of the module, students will have the skills to manage, analyse, and visualise data effectively, preparing them for data-driven roles in research, policy analysis, and other fields requiring strong data literacy.
Quantitative Text Analysis: This module 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 critical social and political questions. By mastering these skills, students can to harness the full potential of automated text analysis in their future careers.
Programming for Social Scientists: This module is 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 creating a social simulation project in teams, allowing students to apply basic programming skills to various 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.
AI and Language Models in Politics: This module on AI and large language models (LLMs) 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, as well as to critically analyse the implications of deploying such models. Throughout the course, students will explore topics including the architecture of neural networks underlying LLMs, 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 LLMs, preparing them for research, development, and policy-making roles where AI and language technologies are due to play an increasing role.
Politics of (Mis)Information: This module delves into the impact of information and misinformation. It investigates how information is produced, disseminated, and influences individuals, organisations, and political institutions. The course examines the effects of political information availability on decision-making and policy outcomes. Students will gain a deeper understanding of the information’s role in society. Learning outcomes include analysing 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.
All details on the programme, along with an overview of the course structure are available (opens in a new window)here.
For further questions about the programme, please contact (opens in a new window)Dr Stefan Müller.
What a Recent Graduate Says about the MSc Politics and Data Science
“I have an undergraduate degree in a social science discipline, so the MSc Politics and Data Science programme provided the perfect opportunity to upskill with programming experience and comprehensive data literacy. The curriculum’s focus on applications of generative AI, machine learning, and large language models has given me invaluable insights into how cutting-edge technology can augment the study of political discourse and decision-making. Through collaborative, hands-on research projects, I quickly gained confidence in using Python and R to tell compelling stories with data. I now have the toolkit to approach coding tasks and navigate an increasingly data-rich world.”
– Robin Rauner, Graduate of MSc Politics and Data Science (2023/24)
“I entered the program with nothing more than an enthusiasm for quantitative research, and I left with a skill set that includes data wrangling, machine learning, and quantitative text analysis. The faculty at UCD is very passionate about education and research, encouraging my peers and me to take the initiative in our learning processes and collaborative projects. At UCD, I found a supportive network and developed a deep appreciation for data and how its study and nuanced interpretation promote informed policies and decisions. The MSc in Politics and Data Science offers a much-needed bridge across disciplines and expertise.”
– Jeanette Garcia, Graduate of MSc Politics and Data Science (2021/22)
ProfCert Programming for Social Scientists
(In person/online, 4 months part-time)
The Professional Certificate in Programming for Social Scientists provides an introduction to computer programming using Python. Python is the most popular programming language among data scientists. It is also an excellent language to learn programming and basic software design skills. Through this course, students will gain extensive knowledge of Python through social science applications, as well as experience in team-based project development and collaborative programming tools. This course is delivered over 12 weeks allowing you to fit your study alongside work, family, or other life commitments.
Course Content and Structure
After watching short online lecture videos, students will come to class – or participate online – to work in groups on exercises and a group project. Especially in the first weeks, the emphasis will be on exercises covering key programming topics. As the course progresses and you gain further programming skills, emphasis will shift towards working on the larger group project.
Career Opportunities
Graduates from this program will be ideally positioned to apply their newly acquired programming skills for careers in government, think tanks, political campaigns, interest groups, and the civil service. Furthermore, the combination of a solid understanding of social science theory with hands-on programming skills brings a unique addition to any data science team, in the corporate sector, the nonprofit sector, or within IT companies.
Contact Us
W: https://www.ucd.ie/spire/study/
T: +353 01 716 8182
E: (opens in a new window)graduatespire@ucd.ie
Apply Now
Apply online at www.ucd.ie/apply. Course code: W527
All details on the program, along with an overview of the course structure are available (opens in a new window)here.
ProfCert Quantitative Text Analysis
(In person, 4 months part-time)
The Professional Certificate in Quantitative Text Analysis introduces students to various computational text mining methods in social science research with a focus on hands-on analysis of real texts. Students will learn to write code that extracts useful information from large textual data sets and develop an independent research project of their choosing that relies on computational text mining methods. This course is delivered over 12 weeks allowing you to fit your study alongside work, family or other life commitments.
Course Content and Structure
This Professional Certificate comprises one 10-credit module Quantitative Text Analysis. Meetings consist of a combination of lectures and lab sessions in which students work through various text-mining methods and tools. Throughout the course, students are encouraged to work on their own interests, by developing an in-depth research project that relies on computational text mining techniques.
Career Opportunities
Graduates from this programme will be ideally positioned to apply their newly acquired computational text-mining skills to redirect their careers in government, think tanks, political campaigns, interest groups, and the civil service. Furthermore, the combination of a solid understanding of social science theory with the technical ability to explore large text data sets, brings a unique addition to any data science team, in the corporate sector, the nonprofit sector, or within IT companies.
Contact us
W: https://www.ucd.ie/spire/study/
T: +353 01 716 8182
E: (opens in a new window)graduatespire@ucd.ie
Apply now
Apply online at www.ucd.ie/apply. Course code: W528
All details on the program, along with an overview of the course structure are available here(opens in a new window).
Other Programs
Furthermore, we are involved in the delivery of both Undergraduate and Postgraduate programs and are keen to supervise potential PhD students interested in applying computational approaches to topics in political science and international relations.
A selection of the programs we are involved in are listed below:
Undergraduate Programs
Master’s Programs
- (opens in a new window)MSc Politics and Data Science
- (opens in a new window)GradDip Politics & Data Science
Ph.D. Programs