Clinical Data Engineering CPD

Year of entry: 2022

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Overview

Degree awarded
PG Credit
Duration
9 weeks (part-time)
Entry requirements

We require an honours degree (minimum Upper Second - 2:1) or overseas equivalent or 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 degree will be considered on an individual basis, and may be admitted at the discretion of the Programme Director.

Full entry requirements

Number of places/applicants
15 places
How to apply

You should apply for this course by completing our online application form . See the 'Advice to applicants' section for details of the supporting documents we require with your form. The deadline for applications is 11:59pm on Friday 16 September 2022 .

If you wish to be considered for a funded place, you will need to submit an application to both the University via the above form and to HEE using this form by 5pm on Monday 22 August 2022 .

Course options

Full-time Part-time Full-time distance learning Part-time distance learning
Modular Y Y N N

Course overview

This CPD unit has been designed to be as flexible as possible for busy healthcare practitioners. It will run over 9 weeks with online, self-directed, and optional face-to-face activities to enable you to develop your data science skills.

  • Learn how to apply data science in practice, and translate data for organisational and patient benefit.
  • Suitable for knowledge and library specialists, nurses, AHPs, healthcare scientists, doctors and other professionals.
  • Optional networking and team working events/activities help maintain motivation and build communities of practice.
  • Study at a university ranked 7th in the UK and in the world top 40 for life sciences and medicine (QS 2022).

Time commitment:

  • Online introductory webinar Monday 3 October 2022, 3pm-4pm. Students can either join at the time of the session or watch the recording later.
  • Optional Hackathon event, Wednesday 16 November 2022 (time tbc). Students will be able to join us either face-to-face in Manchester or online.
We recommend that participants spend between 10-15 hours a week on independent learning and relevant weekly tasks.

Fees

The fee for 2022 entry is £1,300.

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).

Scholarships/sponsorships

Health Education England will fully fund 15 places on the pilot Data Engineering unit. HEE-funded places are open to staff working in, or delivering services to, the NHS in England.

In allocating places, HEE will aim to enable as widespread a representation of healthcare professional groups and roles as possible across the 15 funded places.

To apply for a funded place you need to complete HEE's application form. You will be asked to provide three short supporting statements:

  1. A copy of the personal statement that you supplied as part of your University of Manchester application.
  2. Where will you apply what you learn? - a description and analysis of a problem in your workplace that you will seek to address with what you learn from the Data Engineering module.
  3. What support do you have? - an outline of the support and connections that you can call upon to help you to practically apply what you learn from the module.

Each of the three supporting statements that you provide on page 3 of the form will be scored anonymously and independently by at least 2 members of HEE's team of assessors.

You may wish to prepare your supporting statements in advance and then paste your copy into the form. To help you to prepare you can download a file containing a copy of all of the questions (PDF).

If you wish to be considered for a funded place, you will need to submit an application to both the University via the online postgraduate application form and to HEE using this form by 5pm on Monday 22 August 2022 .

Contact details

School/Faculty
Faculty of Biology, Medicine and Health
Contact name
Postgraduate Admissions Team
Telephone
+44 (0)161 543 4699
Email
School/Faculty
Faculty of Biology, Medicine and Health

Courses in related subject areas

Use the links below to view lists of courses in related subject areas.

Entry requirements

Academic entry qualification overview

We require an honours degree (minimum Upper Second - 2:1) or overseas equivalent or 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 degree will be considered on an individual basis, and may be admitted at the discretion of the Programme Director.

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 on the GOV.UK website .

Specifically, we require a minimum of:

  • IELTS - (Academic): minimum 6.5 overall with 6.0 in writing
  • TOEFL: 575 paper-based
  • TOEFL: 230 computer-based (with a minimum score in the Test of Written English of 6.0)
  • TOEFL: 90 internet-based (with a minimum score of 22 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.

Application and selection

How to apply

You should apply for this course by completing our online application form . See the 'Advice to applicants' section for details of the supporting documents we require with your form. The deadline for applications is 11:59pm on Friday 16 September 2022 .

If you wish to be considered for a funded place, you will need to submit an application to both the University via the above form and to HEE using this form by 5pm on Monday 22 August 2022 .

Advice to applicants

If you are self-funding this course, you should apply to the University via the online postgraduate application form before 11:59pm on Friday 16 September 2022.

Your application form must be accompanied by the following supporting documents.

  • Personal statement - Approximately 500 words reflecting on what is data science and why you want to study it, and how taking this course will impact on your personal and professional development.
  • Full curriculum vitae (CV).

Course participants are expected to have access to a machine of their own to run software required for the course. We recommend a laptop/desktop machine with internet capabilities to access browser-based software.

HEE funding

Health Education England will fully fund 15 places on the pilot Data Engineering unit. HEE-funded places on the pilot module are open to staff working in, or delivering services to, the NHS in England.

If you wish to be considered for a funded place, you will need to submit an application to both the University via the online postgraduate application form and to HEE using this form by 5pm on Monday 22 August 2022 .

Deadlines

  • Funding applications: 5pm on Monday 22 August 2022
  • University of Manchester applications: 11:59pm on Friday 16 September 2022

Course details

Course description

Data scientists are able to ask new questions of data by running analysis methods. This data can be collected and combined from different sources and in different formats.

A large part of data science is the data pre-processing (data wrangling) that first takes place to clean and transform data into a format that can be easily analysed. This can involve creating pipelines and infrastructure to store and process data.

Our introductory Clinical Data Engineering CPD unit aims to introduce concepts of data storage (databases), data access, cleaning/preparing data, and data security and governance.

This unit is suitable for clinical, allied health professionals and others who want to learn more about how they can make use of their data.

This unit will cover:

  • fundamental data types and structures
  • structured and unstructured data
  • the fundamentals of coding for data science
  • how data is modelled in different database systems
  • querying, filtering and cleaning data
  • representing data using data frames
  • data transformation
  • data governance and security.

Course dates

  •  3 October to 2 December 2022 (part-time)

Time commitment:

  •  An online introductory webinar is scheduled for Week 1 on Monday 3 October 2022, 3pm-4pm. Students can either join at the time of the session or watch the recording later, in their own time.
  • An optional Hackathon event in Week 7 on Wednesday 16 November 2022 (time tbc). This event will allow participants to practice some data engineering by working with clinical data sets for analysis and creating a data pipeline. We will be using a hybrid approach for this day event, which means students will be able to join us either face-to-face in Manchester or online.

Other than these planned events, the course is mainly delivered online, with self-directed learning materials that can be accessed at any time.

We recommend that participants spend between 10-15 hours a week on independent learning and relevant weekly tasks.  

Credits

On successful completion of the course, you will receive 15 postgraduate credits that (subject to programme approval) can count towards a PGCert in Clinical Data Science. The PGCert course is expected to start in September 2023, pending approval.

Aims

The unit aims to give you hands-on experience of:

  • applying tools and techniques used to access data in different common formats;
  • transforming and combining this data into a format suitable for subsequent data analysis (such as application of statistical methods/machine learning algorithms) by creating data processing pipelines;
  • using, accessing and querying data in different database storage systems (such as relational and NoSQL databases).

The unit will also:

  • introduce the importance of data security issues both from a technical and legislative perspective;
  • explore the benefits and challenges with accessing and working with health/clinical data.

Special features

Co-designed course content

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 have partnered with leading organisations in health education and care, including the National School of Healthcare Science, Health Education England and The Christie NHS Foundation Trust.

Hackathon event

The course features a hackathon that allows you to practice some data engineering by working with clinical data sets for analysis and creating a data pipeline, which will take place on Wednesday 16 November 2022.

Employability focus

Unit assessments have been designed around providing workplace value.

Data platform-based learning

The course makes use of a learning environment that is also a data platform, allowing access and tools to work with and learn from data, including interactive digital notebooks.

Learn from experts

You will learn from experts who have clinical as well as industry experience working in healthcare, data science and data engineering.

Teaching and learning

The course is mainly delivered online, with self-directed learning materials that can be accessed at any time.

This is also supported by synchronous webinars, forums and digital communication platforms that help students to build an active learning community and benefit from networking. This unit will have one synchronous webinar in week 1, taking place on Monday 3 October 2022, 3pm-4pm via Zoom.

There is also an optional face-to-face day allowing participants to visit and make use of the university campus and equipment, as well as to meet and get to know their fellow students in person.

Sessions are recorded so that students who cannot make synchronous or face-to-face sessions are still able to view any sessions they miss.

Coursework and assessment

This unit is assessed entirely through coursework. You will construct a Data Management Plan (DMP) detailing how a chosen dataset will be stored and processed, along with details of the characteristics of the chosen dataset.

Facilities

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

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk

Careers

Career opportunities

Taking this course will help you develop 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.

Associated organisations

  • National School of Healthcare Science
  • Health Education England
  • The Christie NHS Foundation Trust