Sociology - Social Data Analytics

MSc Social Data Analytics
Graduate Taught (level 9 nfq, credits 90)

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.

Programme Outcomes
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.

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.

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. 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.

How to apply?
The following entry routes are available:

MSc Social Data Analytics FT (W390)
Duration 1 Years
Attend Full Time
Deadline Rolling*

MSc Social Data Analytics PT (W391)
Duration 2 Years
Attend Part Time
Deadline Rolling*

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

90

MSc Social Data Analytics FT (W390): 1 Year Full-Time
MSc Social Data Analytics PT (W391): 2 Years Part-Time

MSc Social Data Analytics (W390) Full Time
EU fee per year - € 7315
nonEU fee per year - € 19900

MSc Social Data Analytics (W391) Part Time
EU fee per year - € 4760
nonEU fee per year - € 9950

***Fees are subject to change

Fee information is available at www.ucd.ie/fees

Next Intake: 2020/2021 September

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.