12 monthsProgramme duration
22,950 GBPTuition Fee/year
Sep, JanStarting Month
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Master's
Study Mode
On Campus
Our MSc in Health Data Science is an interdisciplinary programme that is designed to prepare you for the constantly evolving landscape of data-driven health care.
The programme is based on a research and practice-driven approach, which enables you to engage with real health data. This approach helps you learn how to solve complex computational and analytical health-related problems that are relevant to healthcare, epidemiology and biomedical research.
The curriculum is designed to bridge disciplines and reflect the collaborative nature of health data science itself, with content covering statistical modelling, machine learning, and data analysis and management.
From early in the programme, you will work with tools and technologies used in the field, such as R, SQL and Python; developing your computational literacy alongside your knowledge of clinical, health-related data. The projects you will engage with are highly practical, and reflect real-world challenges, ranging from data handling to predictive modelling in clinical settings.
This MSc is designed to support a diverse group of graduates and professionals with backgrounds and expertise in quantitative sciences. It is particularly suitable for computer science, statistics, physics, maths or biosciences graduates, who are moving into, or looking to apply their skills in a health-related profession. It is also an ideal option for healthcare professionals interested in improving their data-related skills, to get to the next stage of their career or apply for their first job in this field.
While prior experience in statistical programming is helpful, it is not essential. You should either possess foundational knowledge or be motivated to develop these skills as part of the programme.
The programme is based on a research and practice-driven approach, which enables you to engage with real health data. This approach helps you learn how to solve complex computational and analytical health-related problems that are relevant to healthcare, epidemiology and biomedical research.
The curriculum is designed to bridge disciplines and reflect the collaborative nature of health data science itself, with content covering statistical modelling, machine learning, and data analysis and management.
From early in the programme, you will work with tools and technologies used in the field, such as R, SQL and Python; developing your computational literacy alongside your knowledge of clinical, health-related data. The projects you will engage with are highly practical, and reflect real-world challenges, ranging from data handling to predictive modelling in clinical settings.
This MSc is designed to support a diverse group of graduates and professionals with backgrounds and expertise in quantitative sciences. It is particularly suitable for computer science, statistics, physics, maths or biosciences graduates, who are moving into, or looking to apply their skills in a health-related profession. It is also an ideal option for healthcare professionals interested in improving their data-related skills, to get to the next stage of their career or apply for their first job in this field.
While prior experience in statistical programming is helpful, it is not essential. You should either possess foundational knowledge or be motivated to develop these skills as part of the programme.
Programme overview
Main Subject
Health/Healthcare
Degree
MSc
Study Level
Master's
Study Mode
On Campus
Our MSc in Health Data Science is an interdisciplinary programme that is designed to prepare you for the constantly evolving landscape of data-driven health care.
The programme is based on a research and practice-driven approach, which enables you to engage with real health data. This approach helps you learn how to solve complex computational and analytical health-related problems that are relevant to healthcare, epidemiology and biomedical research.
The curriculum is designed to bridge disciplines and reflect the collaborative nature of health data science itself, with content covering statistical modelling, machine learning, and data analysis and management.
From early in the programme, you will work with tools and technologies used in the field, such as R, SQL and Python; developing your computational literacy alongside your knowledge of clinical, health-related data. The projects you will engage with are highly practical, and reflect real-world challenges, ranging from data handling to predictive modelling in clinical settings.
This MSc is designed to support a diverse group of graduates and professionals with backgrounds and expertise in quantitative sciences. It is particularly suitable for computer science, statistics, physics, maths or biosciences graduates, who are moving into, or looking to apply their skills in a health-related profession. It is also an ideal option for healthcare professionals interested in improving their data-related skills, to get to the next stage of their career or apply for their first job in this field.
While prior experience in statistical programming is helpful, it is not essential. You should either possess foundational knowledge or be motivated to develop these skills as part of the programme.
The programme is based on a research and practice-driven approach, which enables you to engage with real health data. This approach helps you learn how to solve complex computational and analytical health-related problems that are relevant to healthcare, epidemiology and biomedical research.
The curriculum is designed to bridge disciplines and reflect the collaborative nature of health data science itself, with content covering statistical modelling, machine learning, and data analysis and management.
From early in the programme, you will work with tools and technologies used in the field, such as R, SQL and Python; developing your computational literacy alongside your knowledge of clinical, health-related data. The projects you will engage with are highly practical, and reflect real-world challenges, ranging from data handling to predictive modelling in clinical settings.
This MSc is designed to support a diverse group of graduates and professionals with backgrounds and expertise in quantitative sciences. It is particularly suitable for computer science, statistics, physics, maths or biosciences graduates, who are moving into, or looking to apply their skills in a health-related profession. It is also an ideal option for healthcare professionals interested in improving their data-related skills, to get to the next stage of their career or apply for their first job in this field.
While prior experience in statistical programming is helpful, it is not essential. You should either possess foundational knowledge or be motivated to develop these skills as part of the programme.
Admission Requirements
2.6+
88+
6.5+
69+
174+
- Applicants should have a 2:2 in a relevant subject such as healthcare, science, technology, engineering, mathematics, computer science, or bio-informatics.
- You should also have experience of analysing quantitative data.
- Significant relevant experience in health data science, or a related field, may be accepted in lieu of a degree and should be evidenced within your applications.
- International Applicants for whom English is not your first language, may require an IELTS score or Swansea University recognised equivalent. If this is the case an IELTS score or recognised equivalent of 6.5 (minimum of 6 in each component) or higher will be needed.
1 Year
Sep
Jan
- Candidates are required to submit references or letter(s) of recommendation for acceptance
Tuition fees
Domestic
10,100 GBP
International
22,950 GBP
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