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Data Science and AI for Health Innovation (Conversion) MSc

University of Liverpool

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University of Liverpool

Course options

2 options available

  • Qualification

    MSc - Master of Science

  • Location

    Liverpool Campus

  • Study mode

    Full time

  • Start date

    28-SEP-26

  • Duration

    12 Months

Course summary

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. Why study this programme 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.

Application deadline

11/09/2026

Tuition fees

Students living in United States
(International fees)

£ 2,667month

Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.

University information

University image

University of Liverpool

University of Liverpool

  • University League Table

    22nd

  • Campus address

    Main Site, The Foundation Building, Brownlow Hill, Liverpool, Liverpool, L69 7ZX, United Kingdom

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Subject rankings

  • Subject ranking

    Business & Management Stu

    22nd out of 124 4

    28th out of 118

  • Entry standards

    / Max 212
    131 62%

    33rd

  • Graduate prospects

    / Max 100
    80.0 80%

    21st

    4

  • Student satisfaction

    / Max 4
    3.19 80%

    43rd

    2

  • Entry standards

    / Max 229
    135 59%

    35th

  • Graduate prospects

    / Max 100
    87.0 87%

    25th

    13

  • Student satisfaction

    / Max 4
    3.09 77%

    47th

    21

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