Course Summary
This programme is for students with a strong interest in the social world and who wish to learn how to effectively apply cutting-edge quantitative methods to solve real-world political, economic, and social problems.
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Career Sectors
This course prepares you for working in the Career Sectors below. Follow the links to get a fuller understanding of the sectors you are preparing for.
Entry Requirements
Applicants should normally have an upper second-class honours degree in one of the Social Sciences. Applications from graduates in other disciplines (e.g. health sciences, business studies, economics, marketing, history etc) who have relevant experience will be considered.
For applicants whose first language is not English and who have not been educated through the medium of English please click here
Students will be required to undergo Garda Vetting, see https://www.tcd.ie/students/orientation/undergraduates/garda-vetting.php for further details
Application Details
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The Student
Career Interests
This course is typically suited for people with the following Career Interests. If these interests do not describe you, this course may prepare you for work you may not find satisfying.
Investigative
The Investigative person will usually find a particular area of science to be of interest. They are inclined toward intellectual and analytical activities and enjoy observation and theory. They may prefer thought to action, and enjoy the challenge of solving problems with sophiscticated technology. These types prefer mentally stimulating environments and often pay close attention to developments in their chosen field.
Career Progression
The MSc in Applied Social Data Science award from Trinity is expected to provide you with a competitive edge in the rapidly expanding job market for data scientists:
You will acquire valuable skills which are sought after in the high productivity sectors, including information technology, consulting, financial services, risk-assessment, logistics, as well as positions in government, NGOs and academia.
You will become fluent in two very popular (and demanded) programming languages, R and Python.
You will gain working knowledge and application experience in advanced statistical analysis, machine learning and important applications such as social forecasting and quantitative text analysis.
You will gain significant experience with methods and approaches to researching social behavioural phenomena within the context of the digital revolution and big data.
A data analytics degree is proving to be an invaluable asset for today’s labour market. Figures from Indeed, an online job site, suggest that the number of job postings for holders of a data science (or equivalent) degree has increased over 344% since January 2013, with a 29% growth rate year over year. Dice, another online job site, claims a 35% year over year growth rate and has labelled data science as a “high-demand skill”. There is general agreement that there is high demand for data scientists, and crucially, demand outstrips supply. For example, in August 2018, LinkedIn reported that there’s a shortage of 151,717 people with data science skills in the U.S. The average salary for a data scientist in the US has been estimated at 106,000 USD by Dice.
A unique trait of the MSc in Applied Social Data Science programme is that it combines rigorous training in methods from computer science and statistics with social science research skills. There is high demand for social scientists who can apply machine learning and statistical methods for data-driven solutions to challenges faced by governments, political groups, and civil society organizations. For instance, political organizations seek employees who can use computational approaches to analyze large-scale digitized collections of political communication, including social media feeds of elected officials, transcripts of parliamentary debates, and government agency press releases. Government agencies seek employees with experience in applying statistical forecasting methods to predict international conflict, terrorism, and disease outbreaks. Non-profit organizations are keen to hire people who are able to apply machine learning and natural language processing methods to help create data-driven solutions for disabled people. These are just a few examples of the jobs our graduates can pursue with the knowledge that they will have gained from the programme.
For non-EU students, it is possible to stay and work in Ireland following course completion using a Stamp 1G visa; see the Trinity Careers Service and the Department of Justice and Equality site for details