Students
Tuition Fee
USD 28,968
Per year
Start Date
Medium of studying
Health Informatics
Duration
12 months
Details
Program Details
Degree
Masters
Major
Health Informatics | Health Information Management | Health Information Technology
Area of study
Health Informatics | Health Information Management | Health Information Technology
Education type
Health Informatics | Health Information Management | Health Information Technology
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
USD 28,968
Intakes
Program start dateApplication deadline
2024-09-01-
About Program

Program Overview


Course Overview

Health Data Science is a rapidly growing discipline, where skilled people are in extremely high demand from industry due to data-led innovations across the sector. Health related data are generated from many sources including observational studies, clinical trials, computational biology, medical records, individual monitoring devices, health care claims, genetic and genomic epidemiology, environmental health, sports science and climate change.

The aim of the programme is to train a new generation of world-leading health data scientists with the essential statistical and computing skills needed to become data science specialists in the health care, biopharmaceutical and medical technology sectors.

This conversion MSc can be tailored around your skills, experience and interests to provide flexible opportunities for those with either strong quantitative backgrounds, or those with an interest in Healthcare that wish to develop their data science and data analytics skills. Graduates will develop the key statistical and computing skills needed to design studies, analyse, interpret and translate research findings to evaluate health interventions, services, programmes, and policies.

The modules will be delivered by recognised experts in pure and applied health data science including statisticians, bioinformaticians, clinicians, mathematicians, health economists, epidemiologists and computer scientists and invited speakers from Medtech, Pharma and Data Science.

The programme is tailored to allow a wide range of student backgrounds, but primarily to:

  • focus skills of those with quantitative backgrounds to needs of the health sector and
  • provide biomedical, healthcare and related professionals a path to retrain or upskill in data science.
  • The courses provide a broad range of skills in statistical modelling, machine learning and clinical research. These skills are brought to fruition in an interdisciplinary capstone research project with either an academic or industry focus.

    You will learn about sources of health related data, regulatory environment, ethics, the tools and skills to collate and analyse diverse datasets across various health domains, develop work-ready skills, and understand the varied roles of health data scientists. The wide range of backgrounds and experience of students will create a dynamic learning environment where students can collaborate with peers from different domains to build those work ready skills.  On completion you will have the core skills and expertise in the use of statistical data science theory, methods and tools for health and related applications.

    Data science skills are in unprecedented demand from many industries, particularly in health care. From precision medicine, to next-generation genomics, to individualised monitoring devices the growth in data collection and data-led decision making is revolutionising health care delivery. If you want to be at the forefront of this revolution in health care in Ireland or globally then this is the MSc for you.





    Applications are made online via the University of Galway Postgraduate Applications System. Selection is based on a combination of the candidate's academic record, CV including research/professional experience and personal statement (see Supporting Documents website). Applicants may be invited to interview.





    Who Teaches this Course

  • Dr Nicola Fitz-Simon
  • [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive] [an error occurred while processing this directive]




    Students are formally assessed through a variety of continuous assessment and end-of-semester written examinations. Continuous assessment include written assignments, data analysis projects (including programming), and individual and group presentations. Assessment of the research project includes a literature review and dissertation, as well as an oral presentation.

    See More
    How can I help you today?