Health Data Analytics is the activity of extracting insights from health data, either to shape national policy, manage local organisations or inform the care of an individual. As more and more data becomes available electronically, the demand for skilled and trained individuals to take advantage of it becomes increasingly urgent.
Students on the Health Data Analytics programme will learn about mathematical and statistical approaches to understanding health data, including operational research, machine learning and health economics. They will learn the fundamentals of how health data is collected, represented, stored and processed as well as how to analyse it effectively and how best to present analyses to have an impact on decisions.
Students undertake modules to the value of 180 credits.
The programme consists of three core modules (45 credits), five optional modules (75 credits) and a research project (60 credits).
A Postgraduate Diploma (120 credits, flexible study 2-5 years) is offered.
A Postgraduate Certificate (60 credits, flexible study over a period of two years) is offered.
Students choose five of the following:
Please note that the optional modules listed here may be subject to change.
All MSc students undertake an independent research project, normally based at their place of work, which culminates in a piece of work written in the style of a journal article.
Teaching and learning
The programme is taught by 'blended learning', and therefore includes interactive online teaching and face-to-face lectures, seminars and workshops including substantial use of examples of real clinical systems. Assessment is through examination, critical evaluations, technical tasks, coursework and project reports, compulsory programming and database assignments, and the dissertation.
Further information on modules and degree structure is available on the department website: Health Data Analytics MSc
Health data analysts are employed by NHS England in a variety of roles, notably within NHS Improvement, assessing policy proposals and evaluating the economic or financial suitability of initatives. They are employed in acute trusts and in public health, mental health and other community-focused organisations to assist in the planning of services and the assessment of demand and to identify improvements in the organisation and management of services. Consultancy organisations providing services to the health sector also employ analysts as do data and IT organisations.
Our graduates will be skilled in the use of mathematical and statistical techniques for the manipulation and analysis of data. They will be familiar with state-of-the-art statistical packages but also have detailed practical experience of working with health data and the specific challenges and responsibilities that it entails. They will understand the processes by which data is collected and have insights into how that impacts its significance. These experiences will equip them to work in the NHS and also in a range of commercial and other organisations dealing with healthcare data.
Health data analysts are employed in interesting and challenging roles in healthcare organisations, government agencies and commercial organisations, including IT suppliers, consultancy organisations and pharmaceutical companies. The demand for skilled analysts is growing and graduates with the right skills and training can choose from a range of exciting and rewarding opportunities.
This programme has been designed in conjunction with the NHS to meet an identified shortage in skilled analysts. The aim is to provide a unique educational experience which not only prepares students for technical roles in analysis but equips them to take on senior roles in NHS organisations. The NHS needs not only more analytics staff, but also managers and decision makers who understand the importance of data and the role that analytics should be playing in shaping policy.
Our programme is delivered by a unique team including mathematicians, computer scientists and statisticians with expertise in the analysis of health data in a variety of forms and for a variety of purposes. The team are highly experienced not just in teaching and research but in the practical application of data analytics to the problems of health and healthcare organisations. We work closely with the NHS and with other commercial organisations to ensure our work is relevant and up-to-date.
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.
Our MSc Health Data Science course aims to create a new breed of scientist who can understand the healthcare sector and medicine, how data is collected and analysed, and how this can be communicated to influence various stakeholders.
The current model of healthcare delivery in the UK is subject to unprecedented challenges. An ageing population, the impact of lifestyle factors and increasing costs mean that the existing approaches may become unsustainable.
This, coupled with a drive towards personalised medicine, presents an opportunity for a step change in healthcare delivery.
To do this, we need to make best use of the health data we collect and create a better understanding of the relationship between treatments, outcomes, patients and costs.
This MSc promotes the need for translational thinking to provide the knowledge, skills and understanding that will be applied across new challenges within healthcare delivery.
Students from a variety of professional backgrounds will benefit from the course, as the structure of the MSc ensures that you will share this knowledge with each other and learn to work in multidisciplinary teams, rather than in specialist silos.
The course has eight taught units covering key skills for health data science. Seven units are core and there is one optional unit depending on training needs and background. For those studying for an MSc, there is also a 60-credit research project.
This course will allow you to:
Research project options
MSc students will have an opportunity to conduct their research project in other settings such as the NHS and the biopharmaceutical industry, as well as academia.
The course covers four main areas that bring together technical, modelling and contextual skills to apply these to real world problems when harnessing the potential of health data.
In each of the units that deliver the key skills, both the importance of the patient and the governance surrounding working in the healthcare environment (especially structures around information governance) is embedded throughout.
Each unit will use case studies provided by existing work and research at the Health eResearch Centre(HeRC). The course will focus on large and complex health datasets (often routinely collected) in environments that safeguard patient confidentiality.
The course will encourage intellectual curiosity, creativity, and critical thinking, providing transferable skills for lifelong learning and research and cultivation of reflective practice.
Through the development of these innovation, critical, evaluative, analytical, technical, problem solving and professional skills, you will be able to conduct impactful work and advance healthcare delivery.
We see learning and teaching as collaborative knowledge construction, which recognises the contribution of all stakeholders (academic staff, service users and carers and students). This is demonstrated in the course through contributions made by these stakeholders through case studies, examples, invited seminars and participation in group work.
A variety of teaching methods will be used within the constraints of the method of delivery. The course will be student centred and will be delivered from the outset using a combination of face-to-face, distance learning and blended learning units.
A range of assessments are used within each course unit and across the course as a whole.
All assessments require you to integrate knowledge and understanding, and to apply this to case studies and the outcomes of each unit.
Assessment will occur in a variety of forms including (but not exclusively) essays, case studies, assessed seminar/tutorial presentations and literature reviews.
Written assignments and presentations have a formative role in providing feedback (particularly in the early stages of course units) as well as contributing to summative assessment.
Online quizzes provide a useful method of regular testing, ensuring that you actively engage with the taught material.
The assessment of tutorials contains an element of self and peer evaluation, so you can learn the skills associated with the effective management of and participation in collaborative activity.
The course also places an emphasis on group work, as this a vital skill for professionals operating in a multidisciplinary area such as health data science, and this is shown in the teaching methods and assignments.
Each unit has a different emphasis on the group work assessment based on the nature of the material being covered, how they are to apply the knowledge and the work they are to complete.
The dissertation for the MSc requires you to undertake an extended written piece of work (10,000 to 15,000 words) that focuses on a specific aspect of health data science.
There is a lot you can do with data in any organisation. With the increase in technology and IOT plus the 'Big Data' revolution the collation of data and the power it holds to transform organisations, ensure health and safety in difficult to reach places, keep ahead of life cycles, drive change and innovation has huge potential for any organisation. Within the oil and gas and energy sectors and related supply chain the revolution of supply and demand is already happening.
If you already work in data either in the energy sector or other related sectors this programme specialises in its application to the oil and gas sector and it is partnered with Common Data Access Ltd which is a not for profit subsidiary of Oil and Gas UK. It provides data management services to the oil and gas industry. The programme is developed with academics at University of Aberdeen and industrial partners and it covers data protection, governance and quality plus project and data management and legal commercial and security aspects of data management.
The programme develops your key data management requirements working in interdisciplinary teams in the energy industry and is sponsored and input by multinationals within those industries. You can study this programme either on campus full time or part time or online part time from anywhere with an internet connection. The part time delivery is designed to fit around your work and life.
Find out more detail by visiting the programme web page for campus delivery and online delivery
Find out about international fees:
Find out more about fees on the programme page
*Please be advised that some programmes also have additional costs.
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MSc Environmental Governance critically analyses some of the key environmental challenges of our time, exploring the connections between environmental governance and policies and the production, distribution and consumption of resources.
The course will develop your ability to apply sophisticated, critical and interdisciplinary sustainability and environmental theories at multiple scales and in different geographical contexts.
As part of the course, you'll have the unique opportunity to collaborate and engage with cutting-edge researchers and world-leading experts on environmental governance, political ecology, Marxist political economy and urban sustainability. You will learn from real-world practitioners, and liaise with external organisations on live policy problems.
This makes MSc Environmental Governance an ideal choice for:
Part-time students complete the full-time programme over 27 months. There are NO evening or weekend course units available on the part-time programme, therefore if you are considering taking a programme on a part-time basis, you should discuss the requirements with the Programme Director first and also seek approval from your employer to have the relevant time off. Timetabling information is normally available from late August from the Programme Administrator and you will have the opportunity to discuss course unit choices during induction week with the Programme Director.
Eight taught units comprise two-thirds of the programme. The remainder of the programme consists of a 12,000 word dissertation on an approved topic. Typical course units comprise two hours a week of seminar or small-group work. Together these units involve a range of formative and summative assessments, including individual and group work, oral presentations and long essays, project work and reports. Coursework is designed to allow you to pursue your particular areas of interest.
In the summer semester, you work independently to undertake dissertation work based on primary and/or secondary data, or else a more philosophical/theoretical dissertation. We encourage you develop research in collaboration with members of the Society and Environment Research Group and external organisations.
Core course units
Past dissertation projects
Every year we have a range of different dissertation topics that reflect students' research interests. For illustration, this list presents some past dissertation topics:
"From the very start, I found all the staff extremely friendly and helpful. There was always someone to speak to, no matter what the problem - as someone who came into studying this subject from a very different undergraduate degree, this made my transition much easier. It also helped that the teaching staff have a real passion for the subject, which I found infectious and inspiring."
Oliver Gibbons, MSc Environmental Governance
The Arthur Lewis Building provides excellent resources including analytical laboratories, studio facilities, workshops, seminar rooms, an on-site cafe and dedicated computer clusters including GIS facilities.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The Information management pathway addresses both the technical challenges of information capture and usage from big data, and the need for its effective and efficient management and analysis within business, scientific, educational, entertainment and organisational contexts. This MSc pathway will examine the entire information management life cycle, including data strategy, management, design and warehousing, data analytics and information governance. In addition to the need to work with huge volumes of data, the pathway will also address multi-modality, including un- and semi-structured data, image and video data, spatial and temporal data, etc.
The pathway consists of two (compulsory) units from the Data Engineering and IT governance ACS theme, three additional compulsory units on various aspects of information management, and one optional unit covering various application areas (such as decision support, text mining, optimisation).
The pathway is taught in collaboration with Manchester Business School (MBS). As such, the programme benefits from the offerings of both schools. MBS is the largest campus-based business and management school in the UK offering world-leading business education informed by leading edge theory and practice. Similarly, the School of Computer Science is renowned as a world-class centre of excellence in computing teaching and research.
IBM has announced that Prof. John Keane from the School of Computer Science at The University of Manchester is one of the winners of its2013 Big Data and Analytics Faculty Awards. He joins 13 other researchers from around the world who will bring together their innovative research for the benefit of curricular development. The award will support technical case studies investigating the design and implementation of big data problems to enhance the postgraduate module in Data Engineering which is central to the Information Management pathway of the Advanced Computer Science and IT management MSc at Manchester.
The (full time version of the) course lasts 12 months, and starts in September. The students take the following core course units:
- Data Engineering (COMP60711)
- Machine learning and Data Mining (COMP61011)
- Information and knowledge management (BMAN71652)
- IT Governance (COMP60721)
- IS Strategy and Enterprise Systems (BMAN60111)
and one course unit from the following three:
- Decision Behaviour, Analysis and Support (BMAN61102)
- Text mining (COMP61332)
- Optimization for learning, planning and problem-solving (COMP61143).
In addition, students follow Research Methods and Professional Skills (COMP60990), which includes academic and professional literacy, ethics, testing, usability, careers, etc. and work on their MSc project. The project is assessed in two parts, through the Project Progress Report (which counts for 85% of the 30 credits for COMP60990) and the Dissertation (60 credits). To continue towards the project for MSc award, students need to pass the taught component (90 credits).
IBM is supportive of the Information Management pathway. The programme fits with some of IBM's core business objectives and also that of some of our clients. (Martyn Spink, University of Manchester Relationship Manager, IBM UK Limited).
We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.