PGCert Clinical Data Science

Applying for an NHSE-funded place

Applications for places fully funded by NHS England (NHSE) must be made directly to NHSE. Please do not complete the University of Manchester application form. Applications for funded places will open on Monday 15 April and close on Monday 13 May .

Further information on eligibility for funded places and how to apply can be found on the National School of Healthcare Science website .

Applying for a self-funded place

To apply for a course you will fund yourself, you should complete and submit our online application form.

The application deadline is 23:59 on Sunday 28 April 2024 . Applications will only be reviewed after this deadline. We reserve the right to close applications once the course is full. For information and guidance, please see how to apply.

Your application form must be accompanied by supporting documents.

A personal statement (approximately 500 words) reflecting on:

• What is Data Science and why you want to study it?
• How taking this course will impact on your personal and professional development?

Please read the full personal statement guidance.

You must also supply a full curriculum vitae, copies of academic certificates, and one professional reference.

Please apply via our online application form.

See the application and selection section for details of the supporting documents we require.

We recommend that you apply as early as possible.

This Clinical Data Science course aims to empower healthcare professionals from across the health and social care workforce, from Knowledge and Library Specialists to nurses, AHPs, healthcare scientists, doctors and beyond, to apply data science in practice. The course is aligned to NHS values, aiming to enhance your ability to work better together and translate data into patient benefit.

The course will support the development of data science, statistics, and machine learning capabilities across the health and social care workforce, leading to a postgraduate qualification in Clinical Data Science.

You will develop your data science skills and drive digital transformation in your practice. The course is introductory and will not train you to become a data scientist, but instead to work with data and informatics teams on digital transformation and research projects, as well as give you skills to make use of data that you may have available in your area.

You will combine your clinical, health and social care knowledge and experience with computer science methods and maths, stats and machine learning skills to make use of your data and add value to your clinical work.

Flexible learning

This course will allow you as much flexibility as possible through the use of online self-directed material and online sessions that are recorded for you to study around your other commitments. You will also benefit from networking and team working events and activities to help maintain motivation and build communities of practice.

Data science tools

You will use a learning environment that is also a data platform, giving you access and tools to work with and learn from data, including interactive digital notebooks.

Expert teaching

You will learn with experts that have clinical and industry experience working in healthcare, data science, machine learning/stats and data engineering.

Co-creation

The course has been co-designed with end users and other stakeholders (including patients) to ensure that it is of real value to working professionals in health and social care. We partnered with leading organisations in health education and care, including the National Health Service, and The Christie NHS Foundation Trust.

You will benefit from blended teaching, which is mostly online with some face-to-face learning opportunities, allowing you to study when you want around your other commitments.

There are synchronous webinars, which are recorded so you can catch up if you miss them. The majority of units have one mandatory face-to-face day of teaching (one unit has two days) in Manchester. In total there is a maximum of five days in-person delivery over the entire course. 

Each of the four 15-credit units equates to around 150 hours of study. You can choose to complete all four units in one year full-time or two units per year over two years part-time.

There will also be the opportunity for networking with other digital leaders and champions, and academic experts.

This course uses real world case studies and interviews with people applying data science in healthcare, allowing you to gain a real insight into how clinical data is used in practice to benefit patients.

The course makes use of authentic assessment to produce artefacts that are likely to occur in practice. So, rather than an academic focus on essays and exams, the units focus on the creation of documents, artefacts and other practices that are likely to occur in real data based projects. These can then be taken away and used by learners as a starting point or template for generating such content for real-world digital transformation and research projects.

The University of Manchester offers extensive library and online services to help you get the most out of your studies.

Taking this course will help you gain the skills and knowledge needed to be at the forefront of the current digital transformation agenda taking place in healthcare.

You will be ideally placed to work with other data centric professionals on digital transformation and informatics projects as well as making better use of datasets that may already be available to you in your area.

The course can also provide a starting point for professionals who are interested in a career change and would like to move into a data science/engineering role in healthcare.