都柏林大学 · 社会数据科学理学硕士 硕士

Entry Requirements

Applicants will be required to hold a 2.1 Honours degree or equivalent in a computational science discipline, and to show evidence for strong interest in social science research; Or to hold a 2.1 Honours degree or equivalent in a social science disciplines and to show evidence for 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.

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

Nearly every aspect of our lives today leave 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. The MSc in Social Data Science is ideal for individuals who want to avail of the excellent employment opportunities created by the progressive digitalisation of society. Most graduates from our programme have gone on to pursue successful careers as analysts or data scientists with national and international private-sector organisations, government agencies, and NGOs, such as: Some graduates have also continued into PhD programmes in a variety of disciplines, both at UCD and abroad. Graduate students are offered the opportunity to either: Undertake an internship (15 credits) and a capstone project (15 credits). ***Internship placements are self-sourced by students with the support of the School and UCD Careers Network Below is a list of all modules offered for this degree in the current academic year. Click on the module to discover what you will learn in the module, how you will learn and assessment feedback profile amongst other information. Incoming Stage 1 undergraduates can usually select an Elective in the Spring Trimester. Most continuing undergraduate students can select up to two Elective modules (10 Credits) per stage. There is also the possibility to take up to 10 extra Elective credits.