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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 °µÍø½âÃÜ hosts several Doctoral Training Partnerships and Centres for Doctoral Training funded by UK Research Councils and provides bespoke training for postgraduate researchers.

Careers Service
The °µÍø½âÃÜ has a dedicated careers service supporting you from the moment you start your degree, to three years after graduation.
Careers advice is embedded into your academic programme through workshops, events, placements, networks – working with the academic staff teaching on your course. We also offer materials, networks and resources online through our 24/7 portal, and a wide-range of activities, opportunities and support centrally in the Careers Service space within the Student Hub.

We are here to help you to explore, connect and succeed.

Discover our Careers Service  

• 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

  This module enables students to undertake an independent research project, applying the knowledge and skills developed throughout their MSc studies. Under academic supervision, students will apply appropriate methodologies, carry out in-depth analysis, and present their findings in a well-structured dissertation that demonstrates critical thinking, technical ability, and academic rigour.

  100% Coursework

  MATH515
  Health Data and Medical Statistics

  You'll learn how to analyse health data from medical studies. We'll teach you how to design clinical trials and other health investigations, taking account of ethical considerations. You'll gain experience in producing professional statistical analysis plans. You'll become expert in using and interpreting output from state-of-the-art software for extracting important insights from health and medical data.

  MATH516
  Machine Learning and Artificial Intelligence for Healthcare 20 credits

  We'll teach you state-of-the-art Machine Learning and Artificial Intelligence techniques for extracting insightful information from health data and medical studies. You'll also learn cutting-edge software to implement all the techniques that you meet. Machine Learning and Artificial Intelligence are becoming increasing important in healthcare and medical practice, and having expertise in them makes you highly employable.

  100% Coursework

  MATH517
  Big Data Visualisation and Analytics 20 credits

  There is an ever increasing amount of Big Data available. You will learn state-of-the-art techniques for extracting valuable information and insights from Big Data. We'll teach you professional software to clean, visualize and analyse complicated datasets. We'll also provide you with experience of professional reporting your Big Data analyses.

  100% Coursework

  MATH518
  Applied Data Modelling and Artificial Intelligence 20 credits

  We'll teach you state-of-the-art modelling and analytics techniques for Data Science, so that you can provide informed strategic advice in a broad range of business and related situations. You'll meet techniques to extract knowledge from data and to update that knowledge when new observations become available. We'll also discuss popular Machine Learning algorithms for making classification decisions.

  100% Coursework

  Optional modules

  COMP5000
  Software Development and Databases 20 credits

  The critical first part of a data science project is extracting and cleaning the data (dealing with missing values, for example.) In this module you will be taught how to use a programming language to do common data science tasks, such as data cleaning, and how to build a Graphical User Interface to a program. You will also learn the design of relational databases, and the extraction of data from a database using SQL.

  100% Coursework

  COMP5006
  Information Security Management & Governance 20 credits

  Navigate the strategic side of cybersecurity. You'll explore how organisations design, implement, and enforce information security governance. From crafting policy to leading audits, this module equips you with the managerial insight to align technical protection with business goals.

  80% Coursework

  20% Practicals

  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

  Discover how machines understand and generate language. From syntactic analysis to transformer architectures, this module explores modern NLP and large language models. You'll build and evaluate systems that can translate, summarise, answer questions and shape the future of communication.

  100% Coursework

  ROCO510
  Computer Vision and Deep Learning 20 credits

  This module provides advanced knowledge of computer vision systems and state-of-the-art deep learning techniques. It covers the theoretical foundations of visual systems, including feature detection, recognition, segmentation, stereo vision, and calibration. Learners will explore robust AI-driven deep learning methods, gaining both theoretical insights and practical skills for computer vision applications.

  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 °µÍø½âÃÜ 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.