MSc Health Data Science and Statistics

The programme is designed to prepare graduates for roles such as: health data analysts, data engineers, data scientists, data managers, data modellers and medical statisticians. The skills developed and knowledge gained during this programme are highly sought after by employers in the healthcare sectors in the UK and globally, including NHS, Clinical Trials Units, healthcare industries, government agencies, research institutions and consultancy units. The skills developed also provide opportunities for employment elsewhere including in the finance and business sectors that invest in healthcare products. The programme also provides a solid foundation for those graduates who would like to continue to PhD study. The University of Plymouth hosts several Doctoral Training Partnerships and Centres for Doctoral Training funded by UK Research Councils and provides bespoke training for postgraduate researchers.

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• Programme overview

• You will take four core modules and two optional modules depending upon your interests and career aspirations, and complete a masters-level project over the summer on a topic of your choice. Your MSc project can be on healthcare data analytics, health informatics or clinical studies or be a multidisciplinary mix of these areas.

  Throughout the programme, you will learn how to master sophisticated analytics techniques and professional software, including R and the tidyverse, Python, and additional software such as SQL/NoSQL databases, to handle and exploit big data, and to work as part of a project team. You will develop conceptual, and practical understanding of topics including Big Data, medical statistics and machine learning. You will gain experience of the design and analysis of health studies, and learn how to provide impactful healthcare insights from a range of medical and clinical studies.

  Core modules

  PROJ518
  MSc Dissertation and Research Skills 60 credits

  You will develop a methodical approach to research that helps propose research projects that are practically realistic and academically worthwhile. A substantial project will be planned and carried out using ethically suitable quantitative and qualitative research methods. The project will be reported through a high quality, scholarly and professional write-up, either as a formal dissertation or journal paper.

  100% Coursework

  MATH515
  Health Data and Medical Statistics

  This module introduces health data and medical studies, and related ethical considerations. It discusses statistical techniques for the design, analysis and interpretation of medical studies. Up-to-date professional software for analysing medical studies is studied. Experience in preparing a professional statistical analysis plan is provided.

  MATH516
  Machine Learning and Artificial Intelligence for Healthcare 20 credits

  This module aims to introduce the cutting-edge techniques in machine learning and artificial intelligence for health data analytics. The practical implementation will be achieved using appropriate software.

  100% Coursework

  MATH517
  Big Data Visualisation and Analytics 20 credits

  Sophisticated techniques are needed to visualize and analyse increasing quantities of Big Data. This module introduces the modern data science techniques and professional software to handle large complex datasets, as well as experience of writing professionally documented code and data analysis reports. Data analysis pipelines, including data cleansing, are used to produce data visualizations and statistical analysis.

  100% Coursework

  MATH518
  Applied Data Modelling and Artificial Intelligence

  This module provides an understanding of modelling and analytics techniques for Data Science. It covers modern data modelling techniques for making strategic decisions in a broad range of Business related practical situations. Students get a hands-on introduction to: Bayesian inference, machine learning, and artificial intelligence. It provides additional practice in making professional presentations.

  Optional modules

  COMP5000
  Software Development and Databases

  This module will provide knowledge and skills in software development and database design. It will cover computational problem solving, abstraction and problem decomposition. The module will enable students to identify appropriate system requirements related to the relational database model.

  COMP5006
  Information Security Management & Governance

  This module looks at the issues surrounding the management and governance of information security within an organisational context. Consideration is given to the need for related policy, analysis of risk, and the management of organisational assets. Coverage also includes legal and personnel aspects of security, giving an overview of the wide range of laws and regulations governing systems & information security.

  MCR702
  Applied Quantitative Research Methods

  This module enables the student to acquire the knowledge and skills to design and conduct a quantitative research project. The students will have advanced understanding of different quantitative research methods, data collection strategies, statistical data analysis techniques, writing skills in quantitative research proposals and final manuscripts.

  MCR706
  Systematic Review

  This module focuses on the appraisal and synthesis of evidence from research literature and documentary sources. Participants gain hands-on experience using JBI software (SUMARI). You will learn more about the systematic review methodology, critically analyse research and text or opinion papers as part of the review process and use software to perform a meta-analysis and meta-synthesis of selected studies.

  COMP5019
  Natural Language Processing and Large Language Models 20 credits

  This module introduces the foundational concepts and applications of Natural Language Processing (NLP) and Large Language Models (LLMs). It covers the theoretical underpinnings of language processing techniques and provides experience in developing and fine-tuning LLM models. Students will learn how NLP and LLMs, such as BERT and GPT, are utilized in diverse domains enabling them to tackle complex challenges effectively.

  100% Coursework

  ROCO510
  Computer Vision and Deep Learning 20 credits

  This module will provide an advanced knowledge of computer vision systems for autonomous robots. It will be underpinned by current theoretical understanding of animal vision systems, feature detection/recognition, and stereo vision/calibration. This module will also introduce the use of deep-learning neural networks (deep feedforward, convolutional, and recurrent) in vision systems.

  50% Coursework

  50% Examinations

MSc Health Data Science and Statistics programme specification September 2025_7378

A 2:2 honours degree, or equivalent, in biology, biomedical science, computer science, chemistry, dentistry, economics, accounting, finance, engineering, epidemiology, health, geography, marine sciences, mathematics, statistics, data science, medicine, nursing, nutrition, physics, public health, psychology, and any other related disciplines in science, engineering, health and technology. Please contact us for individual advice.

English language requirements

We welcome applicants with international qualifications. To view other accepted qualifications please refer to our tariff glossary . We encourage international applicants to contact us for further information and individual advice.

If English is not your mother tongue you need to achieve a 6.5 IELTS with a minimum of 5.5 in any element in a secure English language test.

The University of Plymouth offers pre-sessional English language courses if you do not have this.

Most of our taught programmes begin in September. Applications can usually be made throughout the year, and are considered until programmes are full.

Familiarise yourself with the information required to complete your application form. You will usually be required to supply:

If you require further information take a look at our application guidance.

If you have an impairment, health condition or disability, learn about the additional support the University provides .

Support is also available to overseas students applying to the University from our International Office. Take a look at our how to apply information or email admissions@plymouth.ac.uk.

Once you are happy that you have all of the information required you can apply using our online postgraduate application form (the blue 'Apply' icon on this page).

You will normally receive a decision on your application within four weeks of us receiving your application. You may be asked to provide additional information; two academic/professional references, confirming your suitability for the course; or to take part in an interview (which in the case of overseas students may be by telephone or video conference) and you will be sent a decision by letter or email.

We aim to make the application procedure as simple and efficient as possible. Our Admissions and Course Enquiries team is on hand to offer help and can put you in touch with the appropriate faculty if you wish to discuss any programme in detail.

If you would like any further information please contact the Admissions and Course Enquiries team:

More information and advice for applicants can be referenced in our admissions policy which can be found on the student regulations, policies and procedures page. Prospective students are advised to read the policy before making an application to the University.