Artificial Intelligence and Digital Health MSc

Program Overview

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Artificial Intelligence and Digital Health MSc

Overview

The MSc in Artificial Intelligence and Digital Health offers a comprehensive and interdisciplinary approach to equip students with the knowledge and skills required to succeed in the field of digital health and leverage AI to improve patient care.

Course Structure

• Duration: 2 years
• Attendance: Part-time day - September 2026, Full-time - September 2025, Part-time day - September 2025, Full-time - September 2026
• Fees: More Details
• Alumni Discount: See details
• Duration: 2 years
• Campus: Cavendish, Central London

Course Summary

AI is everywhere, and a solid understanding of AI is required, including in healthcare. This course provides a comprehensive and interdisciplinary approach to equip students with the necessary tools, methods, and experiences in using AI to analyze complex datasets. These datasets will be drawn from various aspects of healthcare, including diagnosis, disease prevention, and wellness promotion.

Top Reasons to Study with Us

• Be at the forefront – the UK is pioneering advancements in AI and Healthcare, with schemes such as the UK Biobank and Genomics England leading the way, making London the perfect place to study this subject, as it’s a hub for global AI companies and institutions such as Google DeepMind and The Alan Turing Institute.
• Interdisciplinary focus – this course provides a unique opportunity to study at the intersection between healthcare, AI, and big data and is suitable for students from either a bioscience or computing background.
• Industry-relevant skills – our connections to external advisors and organisations including AstraZeneca, GSK, and BenevolentAI allow you to gain the practical skills that are in demand in industry.
• Exciting research opportunities – our academic team are engaged in cutting-edge research, giving you the opportunity to collaborate in projects including those led by our Health Data Science research group.
• Aligned with UN Sustainable Development Goals – we focus on global healthcare challenges that impact the entire world, including underrepresented populations, preparing you to improve global healthcare access.

Course Structure

You’ll learn in an integrative way drawing on experiential, interdisciplinary, and community learning alongside collaborative co-creation of solutions to evaluate innovative real-world policies and implement health and wellbeing practices.

Teaching methods include lectures, seminars, workshops, simulations, scientific problem-based learning, and self-directed learning.

Core Modules

• Biobanking for Data Science (20 credits)
• Health Data Science (20 credits)
• Postgraduate Research Methods (20 credits)
• Data Mining and Machine Learning (20 credits)
• Postgraduate Project (40 credits)

Option Modules

• Big Data Theory and Practice (20 credits)
• Communicating Science (20 credits)
• Data Visualising and Dashboarding (20 credits)
• Science, Technology and Commercialisation (20 credits)
• Systems Biology (20 credits)

Professional Recognition

The University of Westminster is a member of the Turing University Network, providing universities with an interest in data science and AI with the opportunity to engage and collaborate with The Alan Turing Institute and its broader networks.

Programme Specification

For more details on course structure, modules, teaching, and assessment, download the programme specification (PDF).

Careers

Whether your background is in biosciences or computing, this course will equip you with the specialist knowledge and skills to succeed in the field of digital health and leverage AI to improve patient care. Not only will you gain the technical skills to do this, but you’ll also learn how to apply these skills in a commercial setting, opening up a range of career possibilities in a city like London, which is a hub for healthcare innovation, technology, and research.

Industry Links

Academics teaching on this course have recognised expertise and experience on an international level, giving you mentorship and insights not just from the course team but from external speakers and guests working within the field of AI and healthcare. We have connections to external advisors and organisations, including AstraZeneca, GSK, and the Alan Turing Institute, ensuring you gain valuable insights and the practical skills that are in demand in the industry.

Graduate Employers

Graduates from this course will be prepared to work in a range of areas, including:

• NHS and other Healthcare providers
• Public and governmental policy bodies
• Small, Medium, and Large Pharmaceutical and Biotechnology Companies
• Pharma or big data-centred consultancy
• Academic research and development laboratories

Job Roles

This course will prepare you for a number of roles, including:

• AI researcher
• Data scientist
• Healthcare IT specialist
• Precision medicine consultant
• Researcher/PhD student
• Digital Health Strategist
• Clinical Informatics Specialist
• Bioinformatics Analyst
• AI Policy Analyst
• Genomic Data Scientist
• Digital Health Project Manager
• User Experience (UX) Designer for Digital Health
• Health Data Analyst
• Machine Learning Engineer in Healthcare

Westminster Employability Award

Employers value graduates who have invested in their personal and professional development – and our Westminster Employability Award gives you the chance to formally document and demonstrate these activities and achievements.

Entry Requirements

• UK: A minimum of a lower second-class honours degree (2:2) in Biomedical Sciences, Applied Biotechnology, Computer Science, or a closely related discipline. Professional qualification of equivalent status and associated work experience or an equivalent qualification deemed suitable by the course team.
• International: A minimum of a lower second-class honours degree (2:2) in Biomedical Sciences, Applied Biotechnology, Computer Science, or a closely related discipline. Professional qualification of equivalent status and associated work experience or an equivalent qualification deemed suitable by the course team.

Fees and Funding

• UK tuition fee: Tuition fees have yet to be confirmed for this course (Price per 20-credit module)
• International tuition fee: Tuition fees have yet to be confirmed for this course (Price per 20-credit module)

Teaching and Assessment

• Scheduled hours: 19%
• Independent study: 81%
• Assessment: Written exams (0%), Practical (23%), Coursework (77%)

Research Groups

Our research achieves real-world impact, and we are proud to claim a rich and diverse profile of high-quality research and knowledge exchange in a wide range of disciplines.

Find out more about the following research groups related to this course:

• Health Data Science
• Computational Vision and Imaging Technology

Supporting You

Our Student Hub is where you’ll find out about the services and support we offer, helping you get the best out of your time with us.

• Study support – workshops, 1-2-1 support, and online resources to help improve your academic and research skills
• Personal tutors – support you in fulfilling your academic and personal potential
• Student advice team – provide specialist advice on a range of issues including funding, benefits, and visas
• Extra-curricular activities – volunteering opportunities, sports and fitness activities, student events, and more

Course Location

With state-of-the-art science and psychology labs and refurbished computer suites, our Cavendish Campus offers our science and technology students a range of learning spaces that are both dynamic and inspiring.

Located in central London, our Cavendish Campus is just a five-minute walk from Oxford Street and Tottenham Court Road.

Related Courses

• Global Public Health with Data Science MSc
• Big Data Technologies MSc
• Data Science and Analytics MSc