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MSc Health Data Analytics

Key facts

Start date September 2019

Duration/mode 12 months full time, 24 months part time

UK/EU fees £10,500 (total)

International fees £22,750 (total)

Entry requirements A bachelor degree with a 2:1 (hons) in a relevant subject.

Language requirements

IELTS 7.0 overall, with no less than 6.0 in writing and 6.5 in all other components

Overview

Training a new generation of Health Data Scientist, Biostatistician, Medical Statistician, and Epidemiologist.

This unique course is designed to train a new generation of data scientists with the specialist skills needed for analysing and interpreting ‘big data’ in the settings of population health and healthcare delivery.

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.

Course benefits

  • UK’s only postgraduate course specialising in the analysis of ‘real world’ health data
  • Expert training in how to overcome pitfalls and malpractices of ‘real world’ data analysis (unique for postgraduate taught programmes world-wide)
  • State-of-the-art training in modelling for prediction and causal inference (unique for UK postgraduate taught programmes)
  • Extensive access to routine health and medical data maintained within Leeds Institute for Data Analytics (LIDA)
  • Novel and clinically-relevant project opportunities, supervised by research leaders, and leading to scientific manuscripts suitable for peer-reviewed publication.

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Course content

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.

Full time MSc students will study modules totalling 180 credits over 12 months. If you study part time you will study fewer modules in each year.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.


For more information and a full list of typical modules available on this course, please read Health Data Analytics MSc Full Time in the course catalogue

For more information and a full list of typical modules available on this course, please read Health Data Analytics MSc Part Time in the course catalogue

Learning and teaching

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:

  • small-group teaching with an expert in the field, including some modules with the opportunity to mix with students from other disciplines;
  • teaching in computer clusters to help you rapidly gain the skills required with statistical packages;
  • online workbooks with relevant links for further research;
  • online audio-visual presentations (vodcasts);
  • online help files and sample data sets with worked examples, which support all the statistical packages;
  • experiential learning as part of the research team for your research project;
  • continuous formative and summative assessment, and feedback.

Assessment

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:

  • informal discussion with tutors
  • written feedback from formative assessments
  • marks obtained in both formative and summative assessments
  • peer-review from presenting projects and data.

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:

  • Online assessment which allows a flexible set of responses, marks the assessment immediately and provides both results and more structured feedback;
  • Short answer questions to test understanding of more complex methods and scenarios;
  • Project reports that allow deeper exploration of a topic;
  • Other methods to fit the skills and knowledge under test, eg presentation of data;
  • For the overall research project, regular meetings with your supervisor to monitor your progress and give feedback.

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Applying, fees and funding

Entry requirements

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.

English language requirements

IELTS 7.0 overall, with no less than 6.0 in writing and 6.5 in all other components. For other English qualifications, read English language equivalent qualifications.

International students who do not meet the English language requirements for the programme may be able to study an English for Academic Purposes pre-sessional course with a progression route to the degree programme. For information and entry requirements, read Pre-sessional programmes.

 

How to apply

Apply (Full time)
Apply (Part time)

This link takes you to information on applying for taught programmes and to the University's online application system.
 
If you're unsure about the application process, contact the admissions team for help.

Admissions policy

Link to admissions policy document

Fees

UK/EU fees: £10,500 (total)
International fees: £22,750 (total)

Read more about paying fees and charges.

For fees information for international taught postgraduate students, read Masters fees.

Part-time fees are normally calculated based on the number of credits you study in a year compared to the equivalent full-time course. For example, if you study half the course credits in a year, you will pay half the full-time course fees for that year.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

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Career opportunities

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:

  • Medical Statistician, Institute for Cancer Research
  • Public Health Intelligence Analyst, Public Health England
  • Senior Analyst, NHS Digital
  • Senior Research Executive, Ipsos MORI
  • Data Consultant, The World Bank
  • Epidemiologist, Thrombosis Research Institute
  • Real Workd Data Scientist, GSK

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.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.

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