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• You should have at least a lower second class (2.2) honours degree (or equivalent) in any subject or five years of relevant work experience. You do not need prior experience in computer programming or data analytics.
• You must also have GCSE Mathematics at grade C or above or grade 4 to 9. Please get in touch with us for details of other acceptable qualifications. You'll need to attain a minimum mark in a diagnostic mathematics test if you don't have an acceptable mathematics qualification.
• If you wish to gain admission on the basis of five years of relevant work experience, you'll be required to attend an online or face-to-face interview and present evidence in the form of a portfolio of work and examples that demonstrate your suitability and aptitude for the course. The evidence should be presented in electronic format and attested by an independent person. The independent person could be a current or former lecturer or an employer with a more senior role than yourself. The University is looking for candidates who can demonstrate a clear style and commitment to their professional practice and who will benefit from experiencing this area of study.
• We'll consider applications where appropriate work experience can be demonstrated in lieu of, or in addition to, the published academic qualifications in line with the University鈥檚 Recognition of Prior Experiential Learning (RPEL) procedures.
• If English isn鈥檛 your first language, you鈥檒l also need IELTS 6.0 with no less than 5.5 in any band (or equivalent). We also accept a range of other English language qualifications 鈥� please visit our English Language Requirements web page for more details.

Where changes are made to material information contained in this course description or a decision is taken to suspend a course between the offer of admissions and enrolment, we will inform applicants at the earliest possible opportunity and will outline the various options available to the applicant.

Data is rewriting the rules of many industries, and healthcare is no exception. Employers such as the NHS, the government, private healthcare providers, and biotechnology giants are scrambling to recruit professionals to help them make sense of it. The demand for workers with specialist health analytics and technologies skills is growing and highly-skilled, competent, creative professionals are needed by organisations across the healthcare spectrum.

Our MSc in Health Analytics and Technologies offers a postgraduate route into this in-demand and varied career. It's an ideal bridge into health data analysis and technologies whatever your undergraduate degree specialisation. Additionally, it's an excellent option if you've worked in a relevant field, gaining degree-level knowledge through experience and self-study rather than formal education.

As a graduate of this master's degree, you'll possess a solid theoretical and practical understanding of health analytics and technologies. You'll be able to demonstrate essential interpersonal and people skills, such as collaboration and teamwork, coupled with commercial awareness and healthcare business-relevant knowledge. You'll also possess high-level academic skills in research, critical thinking and curiosity. Moreover, you'll have the lifelong learning, problem-solving and decision-making skills needed to adapt to new challenges throughout your career.

What can I do with this qualification?

Alternative career options

Depending on your prior qualifications and experience, after graduation, you can also use this master's degree as a stepping-stone into a range of other careers. Some of these roles may require relevant experience and/or postgraduate study. Some possibilities include:

• Leadership and management
• Use of technology in enhancing business and industrial processes
• Solutions driven business and industrial investigation
• Marketing and public relations
• Social media management
• Information systems management
• Cyber security
• Social enterprise
• Policy management
• Education and teaching
• Advising and consultancy

Home/EU Fees

Home students starting this course in the first year will be required to pay a Home fee of 拢5,664 for the academic year 2024/25.

International Fees

Overseas students starting this course in the first year will be required to pay a Overseas fee of 拢15,950 for the academic year 2024/25.

Bursaries

Click here for more information on our Master's Bursaries.

Important note regarding tuition fees for the 2024-25 academic year: EU nationals who meet residency requirements (have settled or pre-settled status) may be eligible for 'Home' fee status. If you do not meet these residency requirements, overseas fees will apply. Irish citizens living in the UK or Ireland will be eligible for 'Home' fee status under the Common Travel Area arrangement. Please read the web page on www.gov.uk for information.

The fees for a student's course of study will be set for the normal duration of that course subject only to inflationary increases – measured by the Consumer Price Index (CPI) recorded in March each year to take effect for subsequent start dates.

We use a blended learning approach, combining face-to-face sessions and practical work as appropriate. You can expect lectures, seminars, tutorials, discussion groups, guest speakers and master classes.

We'll also expect you to undertake considerable guided independent study; for instance, background reading, online activities, assessment work and preparation for sessions. We're committed to supporting you throughout your learning journey. Over time, our guidance will purposefully become less structured and prescriptive. This will encourage you to develop confidence and independence in your studies and take responsibility for managing your own learning time as you increase in autonomy.

Regarding assessment, you can expect a combination of written coursework, project work, oral assessments and portfolios. Summative assessments contribute to your final marks and are your chance to show you've met the learning outcomes for the course. Formative assessments, on the other hand, feature throughout your studies. While they don't contribute to your module or final marks, they inform and support your development by helping you build on your strengths, overcome any perceived weaknesses, and find the study strategies that best support your ultimate success.

This programme adopts a blended learning and teaching style, including online delivery and engagement where appropriate.

We take our social, public and ethical responsibilities very seriously. All our student project work conforms with the University's policies on ethics and uses the University's research ethics procedure before work commences.

Modules

The modules listed below may be a mixture of compulsory and optional. You may not have the opportunity to study all the modules shown as part of the course.

• Professional Practice
• Research Methods
• Project
• Programming for Data Analytics
• Digital Transformation in Health
• Health Informatics
• Data Analysis and Visualisation
• Data Mining and Machine Learning

Assessment methods

Learning Activities

The university will use all reasonable endeavours to deliver your course as described in its published material and the programme specification for the academic year in which you begin your course. The university considers changes to courses very carefully and the university will minimise any changes. Please be aware that our courses are subject to review on an ongoing basis and changes may be necessary due to legitimate staffing, financial, regulatory and academic reasons. The content of course modules and mode of associated assessments may be updated on an annual basis. This is to ensure that all modules are up-to-date and responsive to employment and sector needs. The published course material and the programme specification contain indicative 鈥榦ptional modules鈥� that may be subject to change due to circumstances outside of our control. For this reason, we cannot guarantee to run any specific optional module.