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  • DeadlineStudy Details:

    MSc 1-2 years, full- or part-time

Course Description

This postgraduate degree will build on your existing quantitative knowledge to give you the expertise in statistical analysis, computer science and health research that you will need to become a data scientist in the healthcare sector.

You will develop a thorough grounding in computing and the statistical methods underpinning modern day data science, but with a focus on understanding, applying and adapting it to real life problems in the health domain.

You will develop computing skills required to manage and explore big health datasets, to gain insight into, and inform, health research. Your analytic skills will be developed on real medical data sets, using statistical and computational software such as R and Python.

Alongside this, you will develop your knowledge base of cutting-edge machine learning and artificial intelligence methods, learning how they can be harnessed to answer clinical questions, bringing together the power and potential of computational analytics, statistical thinking, and medical research, to improve health.

Entry Requirements

Good undergraduate degree, minimum second-class honours in a subject with a high quantitative component, e.g. Mathematics, Physics, Economics. Equivalent professional experience may be considered in a relevant field.

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Fees

For fees and funding options, please visit website to find out more.

Programme Funding

There are a number of possible sources of funding: loans and grants, bursaries and scholarships.

Student Destinations

The demand for health data scientists is high and careers sessions will support you looking for you ideal role. Graduates may work in the pharmaceutical industry, health services and university medical research groups and there will be opportunities to apply for PhD programmes.

Module Details

  • Fundamentals of Medical Statistics
  • Foundations of Health Data Science
  • Statistical Modelling (Full-time)
  • Statistical Modelling (Part-time)
  • Statistical Computing and Inference
  • Computationally Intensive Methods
  • Advanced Statistical Modelling (Full-time)
  • Advanced Statistical Modelling (Part-time)
  • Epidemiology
  • Further Topics in Health Data Science

Taught modules will be followed by the Health Data Science Project.

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