Online course

Health Data Science

  • Qualification: PGCert
  • Duration: 12 months
  • Workload: Approx 15 hours per week
  • Next enrolment: September 2022
  • Fees: £5,000
Woman in a laboratory working with data

Introduction

Become the health data science expert

Upskill to meet the growing need for people with the skills to derive insights from health data. 

Health data science is a huge growth area with the explosion in the availability of data and computational power. This PGCert covers the full range of issues in health data science: from governance to epidemiology, from data management to statistical analysis.

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Key features

Learn on the job

Combine your studies with your work and start making an impact from day one.

Build a global network

Learn from health and data colleagues in different settings across the world.

Practise new skills

Bring together the technical, modelling and contextual skills to be a successful health data scientist.

This degree is delivered using real-life case studies provided by the Health eResearch Centre

Health eResearch Centre (HeRC)

Benefits of our approach

  • Focus on large and complex datasets.
  • Encourage intellectual curiosity, creativity and critical thinking.
  • Learn from a joint team of international leaders in the field.
  • Conduct impactful work and advance healthcare delivery.

Key information

  • Delivery

    100% online course developed to fit around your lifestyle and circumstances.

  • Duration

    PGCert - 12 months, part-time.

  • Enrolment dates

    PGCert - Starts Sept 2022. CPD Maths and Statistics for Health Data Science - Sept. CPD Data Engineering for Health Data Science - Nov. CPD Systems and Engineering in Health Data Science - Feb.

  • How to apply

    Due to a system upgrade, our online application form is currently unavailable. We will be launching a new application form in the week commencing 18 October, at which point we will start accepting applications for 2022 entry. If you would like us to email you when the new application form is launched, please submit your details here .

  • Workload

    Approx 15 hours per week

  • Course director

    Dr Matthew Sperrin

Fees and funding

The course fee for the PG Cert for September 2022 is £5000.   

A 5% early application discount is available off your tuition fee if you apply before 24th May 2022. (£250)

The fee for each CPD unit is £1,250.

Entry requirements

We require an honours degree (minimum Upper Second) or  overseas equivalent  in one or the following subjects.

Mathematics or statistics, biological, medical, physical or computer sciences subjects, with sufficient evidence of the relevant units taken.

Find out more

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Course overview

Who this course is for

For the data professional who wants to add value to their team by upskilling in data knowledge, techniques and reporting by studying this flexible 100% online qualification while continuing to work and fitting this study around their work and other commitments.

Bring around a change in big health data reporting and meeting the need for more health data scientists in an increasingly data-led health environment. 

 

What you will learn

  • Bring together the technical, modelling and contextual skills to be a successful health data scientist.
  • Apply these skills to real-world problems, harnessing the potential of health data.
  • Understand the importance of the patient and the governance surrounding working in the healthcare environment.
  • Use case studies provided by existing work and research at the Health eResearch Centre (HeRC) and focus on large and complex health datasets in environments that safeguard patient confidentiality.

Where and when you will study

This fully-online, part-time PGCert means you can study from anywhere in the world and fit it around your day-to-day life. 

You will complete four taught units in 12 months and learn through a mix of interactive teaching and have plenty of opportunities to work collaboratively with your peers. You can choose to undertake single CPD units one at a time, or complete all four to receive your PGCert.

How it will benefit your career

  • Design treatments and allocate resources based on analysis of health and related data.
  • Report on data with more clarity and understanding and develop techniques to support your career.
  • Use skills and knowledge acquired through the course in your job from day one to start advancing in your role and beyond.
  • Practise applying your skills in real-life scenarios through our simulation platform, and be prepared for a range of situations.

Course units

  • Maths and Statistics for Health Data Science

    • Mathematics and Probability Theory
    • The three ‘data science’ tasks, summary statistics, visualisations for data exploration, confidence intervals, hypothesis testing.
    • Prediction and Causal Inference: Linear and logistic regression, assessing goodness of fit, confounding
  • Data Engineering for Health Data Science

    • Programming in Python
    • Version control in Git
    • Relational databases and SQL
  • Systems and Technologies in Health Data Science

    • Health Information Systems and Technologies
    • Data storage and retrieval technologies and data models and architecture
    • System testing and quality assurance: ISO-standards and the system design cycle and methodologies
  • Applied Health Data Science

    • Governance, data sources, quality, technical, ethical and legal issues; linking data sources
    • Data visualisation – techniques, software and presentation style and communication/presentation styles
    • Organisational and change management and risk management

Course structure

This PGCert will upskill you in the fundamentals of health data science. It will equip you with a basic competency in this area so you can understand the operational and governance issues around managing health data, the international context, and fundamental skills in mathematics, statistics and epidemiology to design and analyse simple studies to address business or research questions. 

With a focus on highly applicable skills and knowledge, you will also learn through interactive, state-of-the-art simulations that allow you to experience and practice real-world scenarios. You will complete four taught units in year one. You’ll learn through a mix of interactive teaching and have plenty of opportunities to work collaboratively with your peers.

Course learning aims

In an increasingly data-led health environment you'll bring around a change in big health data reporting and meet the need for more health data scientists.

By studying this course you'll be able to describe how healthcare systems are organised, funded and regulated and how these relate to health data science. You'll be able to demonstrate a critical understanding the flow of data/information and knowledge and its use across the health and social care system.

You'll critically evaluate systems and technologies in relation to current and future thinking around health systems and review the range of systems used to collect, produce and store data.

You'll examine the key issues in information governance, cyber-security and issues of privacy and confidentiality and explain the types of systems and components; network and communication protocols; and databases.

You'll be able to explain the different systems/software development and design methodologies (e.g., agile) and how these fit in the broader cycle of development, deployment and maintenance of healthcare systems.

You'll be able to articulate the importance of interoperability. You'll also be able to describe how data is collected and created to support clinical, research, direct care and commissioning decisions.

You'll be able to demonstrate a critical understanding of the epidemiological and statistical principles used to design studies that provide robust evidence to underpin research, policy, or decision-making.

You'll be able to demonstrate a critical understanding of the flow of data/information and knowledge and its use across the health and social care system, as well as critically evaluating systems and technologies in relation to current and future thinking around health systems.

Teaching and learning

The PGCert program comprises four modules of 15 credits.

  • Data Engineering for Health Data Science will cover introductory programming and data management.
  • Systems and Technologies in Health Data Science introduces issues around coding, governance, linkage and workflows.
  • Mathematics and Statistics for Health Data Science covers foundational techniques in mathematics, statistics and probability needed to analyse simple studies.
  • Applied Health Data Science uses real examples, particularly drawn from electronic health records, to cover epidemiological concepts, applied data analysis, and visualisation.

Coursework and assessment

The course is delivered entirely via online learning, including assessment. Each module of the course runs over 10 weeks, with a nominal 15 hour per week of student work. There are short podcasts, activities and quizzes, interspersed with discussion activities, where you'llcontribute to a discussion board.  

The course has been designed to fulfil the aspirations and needs of all sectors that by developing a world-class health informatics workforce that is integral to multi-professional teams with the technical, methodological and communication skills to be able to deliver high-quality, innovative healthcare delivery, in a range of settings.

Each week during a 10-week module consists of:

  • An overview of the material, presenting the learning objectives for the week (video).
  • Explanatory material (3h of student activity/week) in the form of video lectures, papers/articles, the course text, and links to further resources.
  • Exercises (4h/week). These are a mixture of formative/summative tasks with discussion of these required in the discussion boards. Feedback will be given in the weekly tutorial.
  • Discussion (2h/week). Students are encouraged to discuss the exercises and material in the forums where tutors will facilitate peer learning, providing feedback/input where necessary.
  • Formative Questionnaire. This is to gather students' questions and highlight misconceptions ready for the tutorial.
  • Tutorial (1h/week). Students will video conference with their tutor in groups of 6-8 to discuss and give/receive feedback.

There is also private study of 5 hours per week consisting of:

  • Revision
  • Coursework
  • Further practice (after the tutorials)
  • Independent/further study
The times specified will vary greatly through the weeks. For example, there might be no private study in the first week as no assessments have been set but much longer in week 9 when students will need to prepare for their presentation or submission of coursework

Admissions information

From your initial expression of interest right through to graduation, you’ll receive all the support you need. We can support you with enrolment and subject assistance, administrative logistics and fee options, online learning skills, workload management and special circumstances including a possible professional entry route.

Entry requirements

Academic entry qualification overview

We require an honours degree (minimum Upper Second) or  overseas equivalent  in one of the following subjects:

  • Mathematics or statistics
  • biological
  • medical
  • physical or computer sciences

with sufficient evidence of the relevant units taken.

Please provide two satisfactory professional or academic references and a copy of your CV detailing your full work experience. You will also need to provide a personal statement (approx. 500 words) detailing why you're interested in studying on the course.

If you're applying for a CPD unit, you will still need at least one reference as well as a CV and supporting personal statement.

English language

International students must demonstrate English proficiency through a secure and approved testing system. We ask for English language proof if you are from non-majority English speaking countries (a list of majority English speaking countries, as defined by the UK Home Office, can be found  here  ).

Specifically, we require a minimum of:

  • IELTS  : 6.5 overall (and a minimum of 6 for writing) or equivalent
  • TOEFL: 90 internet-based (with 25 in each component)
English language test validity
Some English Language test results are only valid for two years. Your English Language test report must be valid on the start date of the course.

If you require support with providing an English test, please contact Jessica, your Course Advisor at studyonline@manchester.ac.uk .

Relevant work experience

Non-standard applications for the course from applicants who have significant relevant professional experience and/or where the academic qualification falls below an Upper Second class degree will be considered on an individual basis, and may be admitted at the discretion of the Course Director.

Application and selection

How to apply

Due to a system upgrade, our online application form is currently unavailable. We will be launching a new application form in the week commencing 18 October, at which point we will start accepting applications for 2022 entry. If you would like us to email you when the new application form is launched, please submit your details here.

You'll need to submit:

A completed application form

Two references: One academic and one professional (see our referee report form here )

Personal statement (maximum 500 words) answering the following questions:

  • What attracts you to apply to this course?
  • What do you hope to gain from this course?
  • How will help you achieve your future aims and aspirations?

A recent copy of your CV detailing your professional experience

Degree certificate and official transcripts

Evidence of English language (if applicable, see entry requirements above for more information)

If you have any questions regarding the course or application process, please contact us on  studyonline@manchester.ac.uk  

 

Advice to applicants

The usual sequence of the modules will be:

  • Mathematics and Statistics for Health Data Science (September)
  • Data Engineering for Health Data Science (November)
  • Systems and Technologies in Health Data Science   (February)

They can each be taken as CPD modules and can be taken in any order. 

The module Applied Health Data Science has the previous three modules as prerequisites and cannot be taken as CPD. It is possible to transfer from CPD to the PGCert by completing the remaining modules.

Scholarships and bursaries

Apply before the 24th May 2022 to receive an early application discount of 5% (£250) off your tuition fee.

Additional cost information

Policy on additional costs

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

Regulated by the Office for Students

The University of Manchester is regulated by the Office for Students (OfS). The OfS aims to help students succeed in Higher Education by ensuring they receive excellent information and guidance, get high quality education that prepares them for the future and by protecting their interests. More information can be found at the OfS website.

You can find regulations and policies relating to student life at The University of Manchester, including our Degree Regulations and Complaints Procedure, on our regulations website.