The MSc in Social Data Analytics is a one year taught programme, delivered by schools within the College of Social Sciences and Law (Sociology), and College of Science (Computer Science). It equips students with a range of social scientific, computational, informational, statistical, and visual analytics skills, for the analysis of large or complex data that arise from human interaction. Students will receive training in sociological analysis, as well as core coding and programming skills, allowing them to avail of emergent technologies to manage real-world challenges, and conduct informed decision making. Students can also opt to complete an internship as part of their studies. The MSc in Social Data Analytics is suitable for graduates of social science or computer science programmes, or related disciplines such as psychology, politics, geography, or economics who want to develop their analytical skills further.
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 Analytics 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.
Who should apply?
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
Applicants will be required to hold a 2.1 Honours degree or equivalent, preferably with a social sciences or cognate discipline component, and excellent academic references.
This degree programme included core modules from Computer Science, which is a mathematical subject involving logical understanding and reasoning and therefore applicants must be able to demonstrate a good knowledge of mathematics.
Nearly every aspect of our lives today leaves a digital trace. 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 analytical tools.
On successful completion, the student should be able to:
- Demonstrate a core knowledge and understanding of the fundamentals of social data analytics, 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 social data analytic 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.
What modules can I take?
Core modules include:
- Analytical Sociology
- Social Simulation
- Quantitative Data Analytics and Applications
- Dynamic Social Networks
- Introduction to Programming 1
- Introduction to Programming 2
- Students must also choose one of the following options:
- A. Masters Dissertation
- B. Internship and capstone research project
Optional Modules include:
- Recommender Systems and Collective Intelligence
- Relational Databases and Information Systems
- Spatial Information Systems
- Data Science in Python
- G.I.S. and Data Analysis
- Information Visualisation
- Machine Learning
- Big Data Programming
- Demographic Analytics: Theory and Application
- Research Data Management
- Inequality and Instruments
- Global Migration
- Population Geography
- Comparing Healthcare Systems
- Social Entrepreneurship
- Deep Learning
- Opportunity Generation and Recognition
- Introduction to Artificial Intelligence
Following consultation with MSc in Social Data Analytics 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.
Note: Curricular information is subject to change.
Fees, Funding and Scholarships
MSc Social Data Analytics (W390) Full-Time
- EU fee per year - € 7315
- non-EU fee per year - € 19900
MSc Social Data Analytics (W391) Part-Time
- EU fee per year - € 4760
- non-EU fee per year - € 9950
***Fees are subject to change
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.
- Applicants will be required to hold a 2.1 honours degree (NFQ Level 8 or equivalent), preferably with a social sciences or cognate discipline component, and excellent academic references.
- This programme includes core modules from Computer Science, which is a mathematical subject involving logical understanding and reasoning and therefore applicants must be able to demonstrate a good knowledge of mathematics.
- 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.
These are the minimum entry requirements – additional criteria may be requested for some programmes.
Coming from a background in psychology, I chose to do the MSc in Social Data Analytics because I wanted to develop my social research and methodology skills in ways that incorporate new and exciting technologies emerging in the field of ‘big data’. I feel that in providing for this, the course is unique. During my time at UCD, I have been exposed to a variety of computer science techniques for data analysis which I have been able to apply in complementary social science modules. To my pleasant surprise, skills like programming have all been taught at a reassuring pace for a novice like myself. By the close of the first semester, I was already being called for interviews in well-known firms in sectors and for positions that would have been closed to me before embarking on the course. I highly recommend the MSc to anyone who is interested in using technology to do social science in entirely new ways.
Killian Mc Loughlin, Student 2017/2018
About the School
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