Health Data Science
Basic Information
- Course ID
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8d83267b-1e85-489a-8dbb-d3675b8a5991- Provider
- University of St Andrews
- Type
- postgraduate
- Academic Year
- 2026
- Source
- ucas
- Created
- 2/22/2026, 8:38:10 AM
- Updated
- 3/27/2026, 11:05:16 AM
Other Options for this Course
No other options
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"modules": "Semester 1:\nThe MSc is structured around a mixture of compulsory and optional modules: \n\nDigital Health Principles: explores the theoretical underpinnings of digital health; students consider different forms of health data, technologies and methods for processing and analysis, and the integration of digital data in clinical decision making. \nStudents will normally be required to complete the following modules unless they have significant experience in statistics and programming: \n\nIntroductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis. \nand one of the following: \n\nObject-Oriented Modelling, Design and Programming: introduces and reinforces object-oriented modelling, design and implementation to provide a common basis of skills, allowing students to complete programming assignments within other MSc modules. \nProgramming Principles and Practice: introduces computational thinking and problem-solving skills to students who have no or little previous programming experience.\n\nSemester 2:\nDigital Health Practice: looks at the practical applications of digital health; students learn practical skills in medical data analysis and the use of digital technologies to address healthcare challenges. \nBiomedical imaging and sensing: covers the fundamentals of image and signal processing, with how the different types of medical imaging modalities work (such as MRI, CT, PET, ultrasound and optical imaging) along with their uses and limitations in a clinical setting. Finally convolutional neural networks (CNNs) are introduced as a way to classify medical images. \nAll students will normally take modules in programming and quantitative methods in Semester 1 unless they have a sufficient background in computer science and data analysis or statistics. These modules complement the core modules. \n \nOptional modules:\nAll students will normally take modules in programming and quantitative methods in Semester 1 unless they have a sufficient background in computer science and data analysis or statistics. These modules complement the core modules. \n\nAlongside the compulsory modules and the programming and quantitative methods modules, you will complete one or two other optional modules. Optional modules allow you to shape the degree around your own personal and professional interests. \n\nOptional modules are expected to be offered in the following areas: \n\ndata analysis \ninformation visualisation and visual analytics \nmachine learning \nprogramming principles and practice. \nOptional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students (see the University’s position on curriculum development). \n\nThe final part of the MSc is the end of degree project. This takes the form of a period of supervised research where you will explore a health data science topic in depth. \n\nThrough the project you will show your ability to undertake sustained critical analysis, develop and improve your research skills, and produce an extended piece of written work that demonstrates a high level of understanding of your area of study. \n\nYou can choose to present your end of degree project as one of the following: \n\na policy report that emphasises your ability to critically assess digital health policy and make convincing recommendations for policy changes \na multi-media portfolio that emphasises your ability present digital health concepts in exciting and engaging ways \na written dissertation that emphasises your ability to plan and execute academically rigorous research. \nIf students choose not to complete the project requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma. By choosing an exit award, you will finish your degree at the end of the second semester of study and receive a PGDip instead of an MSc.",
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