Social Data Science

MSc Social Data Science

Graduate Taught (level 9 nfq, credits 90)

The MSc in Social Data Science is a one year taught programme with strong interdisciplinary features and components across social and computational sciences. It equips students with a range of social scientific, computational, informational, statistical, and visualisation skills, for curation and analysis of large or complex data that arise from human activities and interactions in the digital world. Students will receive training in sociological analysis, as well as core coding and programming skills, allowing them to avail of emergent computational methods and technologies to tackle real-world societal challenges, and inform decision making processes. Students may opt to complete an internship as part of their studies. The MSc in Social Data Science is suitable for graduates of social science or computer science programmes.

Module Trimester Credits

Stage 1 Core Modules

SOC40640 Social Simulation: Methods and Models Autumn 10

SOC41200 Research Design Autumn 10

SOC41130 AI and Society Spring 10



Stage 1 Options - A)30CR:

Students must choose a maximum of 30 credits of which 10 credits must be at level 4 from the list of options. Students must select 10 credits in the Autumn and 20 credits in the Spring Trimester from the list of Options. The maximum amount of credits allowed per one trimester is 30.

COMP10010 Introduction to Programming I Autumn 5

COMP10030 Algorithmic Problem Solving Autumn 5

COMP40610 Information Visualisation Autumn 5

COMP47340 Computational Thinking (Conversion) Autumn 5

COMP47460 Machine Learning (Blended Delivery) Autumn 5

GEOG40770 GIS for Environmental Assessment Autumn 5

POL40950 Introduction to Statistics Autumn 10

SOC30710 Historical Sociology Autumn 10

SOC30740 Sociology of climate change Autumn 5

SOC40330 Workshop in Qualitative Research Autumn 10

SOC40720 Organised Violence and Society Autumn 10

SOC41160 Global Solutions and Applied Social Change Autumn 10

SPOL40470 Comparing Healthcare Systems Autumn 10

STAT30340 Data Programming with R Autumn 5

STAT40400 Monte Carlo Inference Autumn 5

COMP47670 Data Science in Python (MD) Autumn and Spring (separate) 5

COMP47750 Machine Learning with Python Autumn and Spring (separate) 5

COMP10020 Introduction to Programming II Spring 5

COMP30110 Spatial Information Systems Spring 5

COMP47580 Recommender Systems & Collective Intelligence Spring 5

CSOC30030 Advanced Computational Social Science Spring 5

ECON42720 Causal Inference & Policy Evaluation Spring 5

POL42050 Quantitative Text Analysis Spring 10

POL42340 Programming for Soc Scientists Spring 10

SOC40620 Nationalism and Social Change Spring 10

SOC40790 Art, Knowledge & Social Change Spring 10

SOC41060 Religion in Compar Perspective Spring 10

SOC41120 Human Development Challenges in the Global South Spring 10

SOC41150 Queering Global Challenges Spring 10

SOC41170 R.A.G.E. - Remembrance, Activism, Genocide, Emotions Spring 10



Stage 1 Options - B) Min 1 of:

Students must either take SOC40140 OR, alternatively both SOC41010 AND SOC41020. A maximum of 30 credits in total must be chosen from this section.

SOC40140 Dissertation Summer 30

SOC41010 Capstone Research Project Summer 15

SOC41020 Internship Summer 15

Applicants will be required to hold a 2.1 Honours degree or equivalent in a computational science discipline, and to show evidence for strong interest in social science research; Or to hold a 2.1 Honours degree or equivalent in a social science disciplines and to show evidence for strong interest in obtaining, or existing computational skills. Additionally, excellent academic references are required.

This degree programme includes modules from Computer Science, which involves logical understanding and reasoning and therefore applicants must be able to demonstrate good evidence of algorithmic thinking.

All applicants will be assessed on a case-by-case basis and relevant work experience will be taken into account, so that in certain cases an award at a 2.2 classification may be considered.

Students whose first language is not English will need a recognised English language qualification. On the International English Language Testing System (IELTS) students will need to achieve an average score of 6.5 over all components and a minimum of 6.0 in each band on the Academic Version. More details are available through the UCD International Office at http://www.ucd.ie/international/study-at-ucd-global/ucdenglishlanguagerequirements/



These are the minimum entry requirements – additional criteria may be requested for some programmes



You may be eligible for Recognition of Prior Learning (RPL), as UCD recognises formal, informal, and/or experiential learning. RPL may be awarded to gain Admission and/or credit exemptions on a programme. Please visit the UCD Registry RPL web page for further information. Any exceptions are also listed on this webpage. https://tinyurl.com/2ae2ffax

1 year full-time, 2 years part-time.

Commencing September 2025

Careers & Employability

A wide range of different organizations including government departments, semi-state bodies, private companies in IT, finance and consultancy, as well as sectors such as education, health and social welfare are now exploring the benefits of combining large and complex data resources, including administrative data, for decision making and resource use. The MSc in Social Data Science at the UCD is ideal for graduates who want to upskill and avail of these excellent employment opportunities. It is designed to enable individuals to combine their social science and/or cognate training with strong technical and analytical skills, and to exploit the wide range of digitised and digital data now accessible by public and private sector organisations.