Applied Social Data Science (M.Sc.)

Overview

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.

Course Overview

The MSc in Applied Social Data Science is a one-year, full-time programme which introduces students to fundamentals in quantitative social science research methods and state-of-the-art analytic approaches from the fields of statistics and machine learning. Graduates of the course will acquire a rich repertoire of social scientific research design skills---grounded in the scientific method---and data analytic methods that are widely sought after in the private, public, and non-profit sectors.

Is this course for me?

The programme is based in Ireland’s highest ranked Department of Political Science. Our department enjoys a strong reputation internationally for its staff who rely on quantitative research methods, and who are well published in leading peer-reviewed academic journals. Staff research agendas include core skills offered in the Applied Social Data Science programme, including computer programming, statistical modelling, machine learning, quantitative text analysis and forecasting.

• You will acquire fluency in widely used programming languages and gain the skills to collect and manage big data-sets.
• You will learn how to apply and critically assess computational and statistical models to solve real-world social problems.
• Seminars and class discussions will provide you the opportunities to enhance your critical thinking skills and acquire an in-depth understanding of quantitative social scientific research.

Course Structure

The one-year programme covers a wide range of core modules which will help you expand your quantitative research methods toolkit.

• First Semester: To start the course, you will take modules in computer programming, applied statistical analysis and research design.
• Second Semester: Next, you will dig deeper by taking modules in machine learning, forecasting methods, and quantitative text analysis.
• Dissertation: Finally, you will complete a key piece of research related to your field of study over the summer months.

Please visit the Course Content section for more details. All modules are taught around a weekly seminar with tutorial sessions and assessed with a mix of homework, exams, and research papers. Students are expected to bring their own laptop (Mac/Windows/Linux) for use in seminars and tutorials throughout the course; note - tablets are not suitable. For minimum laptop specs, please see this helpful guide

Career Opportunities 

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

Further Information

Enquiries can be made to the HCI and Postgraduate Programmes Coordinator or the Course Director of the Postgraduate Diploma in Applied Social Data Science, Dr Constantine Boussalis. Please make sure to read the Frequently Asked Questions before emailing.

How to Apply

Applications for 2023-24 will remain open until 31st July 2023. You are advised to apply as early as possible.
Please visit the Admissions Requirements section for full details of the application documentation and access to the online application portals.
Click Here for further information on modules/subject.