P.Grad.Dip. Applied Social Data Science
Course Description
The Postgraduate Diploma in Applied Social Data Science (ASDS) is a one-year, full time programme commencing in September 2021. Its aim is to introduce students to the application of state-of-the-art analytic approaches from the fields of statistics and machine learning to the study of social scientific questions. Graduates of the course will acquire rich repertoire of social scientific research design skills and data analytic methods that are objectively in very high demand in the private, public, and non-profit sectors. The course is unique in Ireland as it provides in depth knowledge on advanced computational skills, ranging from statistical analyses of datasets to training artificial intelligence algorithms, using practical and applied approaches. So far, existing data science programmes require extensive statistics backgrounds for applicants. This course aims to train students who have limited quantitative research backgrounds but strong interests in enriching their methodological toolkit to contribute substantively to evidence-based, big data research activities in the modern economy. The course, therefore, will admit applicants at a graduate 2.1 level with some quantitative methods training from their undergraduate degree.
Course Description
The Postgraduate Diploma in Applied Social Data Science (ASDS) is a one-year, full time programme commencing in September 2021. Its aim is to introduce students to the application of state-of-the-art analytic approaches from the fields of statistics and machine learning to the study of social scientific questions. Graduates of the course will acquire rich repertoire of social scientific research design skills and data analytic methods that are objectively in very high demand in the private, public, and non-profit sectors. The course is unique in Ireland as it provides in depth knowledge on advanced computational skills, ranging from statistical analyses of datasets to training artificial intelligence algorithms, using practical and applied approaches. So far, existing data science programmes require extensive statistics backgrounds for applicants. This course aims to train students who have limited quantitative research backgrounds but strong interests in enriching their methodological toolkit to contribute substantively to evidence-based, big data research activities in the modern economy. The course, therefore, will admit applicants at a graduate 2.1 level with some quantitative methods training from their undergraduate degree.
