The qualifications and exam results you'll need to apply for this course.
You'll need to demonstrate competence in the use of English language, unless you’re from a majority English speaking country .
We accept a variety of international language tests and country-specific qualifications .
International applicants who do not meet the minimum required standard of English language can complete one of our Pre-Sessional English courses to achieve the required level.
Do you need to complete a Pre-sessional English course to meet the English language requirements for this course?
The length of Pre-sessional English course you’ll need to take depends on your current level of English language ability.
If you don’t meet our English language requirements, we can use your most recent IELTS score, or the equivalent score in selected other English language tests , to determine the length of Pre-sessional English course you require.
Use the table below to check the course length you're likely to require for your current English language ability and see whether the course is available on campus or online.
If you’ve completed an alternative English language test to IELTS, we may be able to use this to assess your English language ability and determine the Pre-sessional English course length you require.
Please see our guide to Pre-sessional English entry requirements for IELTS 6.5 overall, with no component below 6.0, for further details.
Build confidence in statistics, programming and responsible AI for healthcare innovation. Our MSc Data Science and AI for Health Innovation (Conversion) is designed for students from a wide range of academic and professional backgrounds who want to transition into the rapidly growing field of health data science and artificial intelligence. This programme provides a supportive introduction to statistics, programming, machine learning and health data analysis, helping you develop both technical expertise and confidence in applying data science approaches to real-world healthcare challenges.
Healthcare is increasingly shaped by data science, artificial intelligence and digital technologies. From electronic health records and wearable devices to AI-assisted diagnostics and public health monitoring, healthcare systems now generate vast amounts of data with enormous potential to improve patient care and health outcomes.
As the use of healthcare data and AI continues to expand, there is growing demand for professionals who can analyse, interpret and communicate complex information responsibly and effectively.
This programme is specifically designed for students who may not have previous quantitative training but are motivated to develop expertise in health data science and artificial intelligence. Through a supportive and carefully structured learning experience, students progressively build confidence in statistics, coding, computational methods and data analysis.
The programme combines core foundations in statistics, programming and health data science with opportunities to explore specialist areas including machine learning, artificial intelligence, prediction modelling and healthcare evaluation.
Designed around flexibility and student support, the programme allows students to tailor their studies around their own interests and future career ambitions while developing highly valued analytical, computational and professional skills.
The programme also has strong links with the Civic Health Innovation Labs (CHIL) , an internationally recognised multidisciplinary research centre based at the University of Liverpool. CHIL brings together experts from academia, the NHS, local government, charities and industry to develop responsible approaches to data use and AI for health and society.
Graduates from the programme are well placed for careers across healthcare, digital health, public health, research and healthcare innovation, with opportunities continuing to grow rapidly both within the UK and internationally.
Build confidence in a supportive learning environment
This programme is designed specifically for students transitioning into health data science from a wide range of backgrounds. Teaching is carefully structured to help students progressively develop confidence in statistics, programming and analytical thinking.
You will learn within a welcoming and collaborative academic environment where curiosity, professional development and student support are actively encouraged.
Tailor your learning to your ambitions
As your confidence and experience develop, optional modules allow you to explore areas aligned with your own interests and career ambitions, including applied statistics, machine learning, healthcare evaluation and artificial intelligence.
This flexibility helps students develop distinctive profiles suited to careers across healthcare, industry and research.
Learn from experts who care
You will study alongside approachable staff with expertise across statistics, health data science, artificial intelligence and healthcare research.
Teaching is enriched by guest lecturers and research collaborations connected to organisations including the NHS, industry and the Civic Health Innovation Labs (CHIL), helping students connect learning to real-world healthcare challenges and innovation.
This programme is designed for students who are interested in health data science and artificial intelligence but do not have prev