Training a new generation of leaders in Health Data Science, Biostatistics, Medical Statistics, and Epidemiology.
This unique course is designed to train a new generation of data scientists with the specialist skills needed foranalysing and interpreting ‘big data’ in the settings of population health and healthcare delivery.
The course is delivered by expert staff at the Leeds Institute for Data Analytics (LIDA) and is unique in the UK for specialising in the analysis of real-world health data for causal inference. LIDA is an internationally recognised centre for data science and recently partnered with the Alan Turing Institute, the UK's national institute for data science and artificial intelligence. Module lecturers Prof Mark Gilthorpe and Dr Peter Tennant are themselves Fellows of the Alan Turing Institute, in recognition of their world-leading contributions to health data science.
The data revolution promises to transform our understanding of health and deliver new insights into the development of therapies and delivery of health care. Unlocking this potential requires a similar revolution in data analytic skills that combines new and emerging statistical skills with advanced scientific and critical reasoning. Our course provides the professional and technical skills training to support the development of a health research career in your chosen area.
Our course is designed for recent graduates with an interest in health data science including those seeking a career in quantitative health research, either within industry, the public sector, or academia, or advanced data analytics within a healthcare or health intelligence setting. Upon graduating you will be at the forefront of the discipline of health data science and have advanced knowledge and skills appropriate to a range of careers involving the analysis and interpretation of ‘real world’ health data.
Recent graduate destinations include:
Many of our students also chose to study advanced postgraduate research degrees (such as PhDs and MDs) before going onto more senior positions in industry or the public sector.
There is demand for students and academic staff with excellent statistical skills, an enquiring attitude, and a broader understanding of the research environment. Our graduates are attractive to employers in academic research, health and social care and industry. Prospective employers value their technical expertise and research understanding. They also value the professional skills gained, including writing a grant application and a paper of submission quality.
This unique MSc offers an exciting blend of core and optional content to provide a cutting-edge grounding in modern health data science while allowing you to specialise in a range of areas, such as clinical trials, machine learning, spatial analytics, and genetic epidemiology.
Our innovative Professional Skills for Health Data Analysts module will equip you with the skills and experience to work effectively in research, public health or health services research. It covers; ethics, academic writing for publication, consultancy, management and leadership skills.
The course will also provide you with strong foundations in the skills and knowledge of data analytics with relevance to health. We stretch you to acquire and implement advanced techniques through optional modules. These modules allow your learning to be tailored towards discipline-specific paths appropriate to your future career.
Universities in the United Kingdom use a centralized system of undergraduate application: University and College Admissions Service (UCAS). It is used by both domestic and international students. Students have to register on the UCAS website before applying to the university. They will find all the necessary information about the application process on this website. Some graduate courses also require registration on this website, but in most cases students have to apply directly to the university. Some universities also accept undergraduate application through Common App (the information about it could be found on universities' websites).
Both undergraduate and graduate students may receive three types of responses from the university. The first one, “unconditional offer” means that you already reached all requirements and may be admitted to the university. The second one, “conditional offer” makes your admission possible if you fulfill some criteria – for example, have good grades on final exams. The third one, “unsuccessful application” means that you, unfortunately, could not be admitted to the university of you choice.
All universities require personal statement, which should include the reasons to study in the UK and the information about personal and professional goals of the student and a transcript, which includes grades received in high school or in the previous university.
A bachelor degree with a 2:1 (hons) or equivalent qualification in a quantitative or scientific subject area with substantial mathematical, statistical or numeracy components. We also consider working experience (two years or more) of research in a quantitative subject area.
You’ll have access to the very best learning resources and academic support during your studies. We’ve been awarded a Gold rating in the Teaching Excellence Framework (TEF, 2017), demonstrating our commitment to delivering consistently outstanding teaching, learning and outcomes for our students.
We mix face-to-face teaching with technology to enhance your learning experience. Self-directed online learning lets you study at a pace that suits you, whilst face-to-face support allows you to explore individual areas of difficulty and extend your understanding.
You’re likely to experience:
We understand the importance of assessment and feedback in your learning. We provide assessment in as many modules as possible so that you can gauge your understanding of the key concepts.
You’ll get feedback in a variety of ways. These include:
Each module contains a summative assessment component. Some of these will be done via continuous in-course assessment, and some as end-of-module assessment.
Our assessment and feedback will use a number of methods: