MSc Social Data Science
Dublin, Ireland
MSc
DURATION
1 year
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
EARLIEST START DATE
TUITION FEES
EUR 22,600 / per year *
STUDY FORMAT
On-Campus
* full time non-EU fee per year - € 22600; EU fee per year - € 9300 | part time non-EU fee per year - € 11300; EU fee per year - € 5600
Fast-track counseling
By contacting the school, you'll get access to free priority counselling for any study and application questions.
Key Summary
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 the 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 themselves 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.
Who should apply?
Full-Time option suitable for:
- Domestic (EEA) applicants: Yes
- International (Non-EEA) applicants currently residing outside of the EEA Region: Yes
Applicants will be required to hold a 2.1 Honours degree or equivalent in a computational science discipline, and to show evidence of strong interest in social science research; Or to hold a 2.1 Honours degree or equivalent in social science disciplines and to show evidence of 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.
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 contact our Admissions team!
What modules can I take?
Core modules include:
- AI and Society
- Social Simulation
- Research Design
- Data Programming with R
- Sociological Thinking in the Digital Age
- Students must also choose one of the following options:
- A. Masters Dissertation
- B. Internship and capstone research project
Optional Modules Include:
- Introduction to Programming I
- Algorithmic Problem Solving
- Databases and Information Systems I
- Computational Thinking (Conversion)
- Machine Learning (Blended Del)
- GIS for Environmental Assessment
- Introduction to Statistics
- Policing & Social Conflict
- Health Illness and Society
- Organised Violence and Society
- Critical Race & Decolonial Theory
- Comparing Healthcare Systems
- Monte Carlo Inference
- Data Science in Python (MD)
- Machine Learning with Python
- Creativity & Innovation
- Introduction to Programming II
- Spatial Information Systems
- Information Visualisation
- Rec Sys & CI
- Advanced Computational Social Science
- Quantitative Text Analysis
- Programming for Social Scientists
- Social Dynamics and Networks
- Qualitative Research
- Nationalism and Social Change
- Population and Society
- Sciences,Technologies & Societies
- Religion in Comparative Perspective
Following consultation with MSc in Social Data Science Programme Director, a student may be able to substitute more advanced modules for specific core modules where the student can demonstrate sufficient prior learning in those areas.
***Modules are subject to change
Nearly every aspect of our lives today leaves digital traces. Leveraging this massive sea of information requires both a judicious understanding of how substantive and social scientific questions drive the data analysis and the skill and training to use scalable data science tools.
On successful completion, the student should be able to:
- Demonstrate a core knowledge and understanding of the fundamentals of social data science, data requirements and techniques.
- Construct, synthesize, evaluate, interpret, and report theories and evidence in an open, analytical and critical manner.
- Apply problem-solving skills in a variety of different contexts.
- Apply appropriate data science techniques to address domain-specific research problems.
- Discuss, present and communicate their research ideas, data and results within a group setting and in one-to-one communication.
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.