Data Visualisation: Knowledge Transfer (April 2024)
Data visualisation, in general terms, is a tangible representation of data that provides an accessible means for analysing, understanding, and communicating the trends, outliers, and patterns of data for and across sectors and audiences. This course explores the communication of data relevant to health, social and care services settings through visualisations for exploration, analysis and related communication media. Visualisation can be a powerful means of sharing and communicating service user data to a range of audiences, such as driving policy development or improving stakeholder or broader public understanding. The course will explore theory, application, design and evaluation techniques that can be used to visualise and accessibly communicate data in various ways, such as combining vignettes taken from individual stories with data derived from official sources such as government statistics. Students will be introduced to several global projects that communicate health, social, and care services data in this way and will have the opportunity to develop their small data visualisation project.
With data volumes increasing exponentially, an increasing focus on interdisciplinary approaches to complex problems, and an ever more tech-savvy general public, those working in health, social and care services can no longer rely solely on data presentation tools such as spreadsheets and tables. Data visualisation gives organisations and individuals the means to share important information, sometimes in real-time, by telling data stories. Data visualisation curates data into a form that is accessible and which can more easily highlight current utilisation, trends and outliers. Well curated data visualisation will allow individuals and organisations to tell a story. Unlike more traditional data representation forms, data visualisation aims to remove the noise from data and highlights usable information. This course will enable students to describe a visualisation problem within target users and global environments, explore the data visualisation, discuss and design appropriate and accessible visualisation concepts, and implement and critically reflect on their own and other's designs.
This course is for anyone working in health or social care or computational roles who is interested in starting a career in data science OR graduates who are seeking to develop data science skills that can be applied in health, social and care services.
This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject – no prior knowledge is needed. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis and reflection.
As this course is designed mainly for health and care professionals, we expect our students to have qualifications or work experience in such environments (e.g. NHS National Services, Acute/Community/Public health), Third sector organisations, Social Services, Nursing homes, pharmaceutical companies, diagnostic laboratories, etc.). An understanding of the fundamentals of maths and statistics (at Higher level) would be advantageous but is not a prerequisite for joining the course.
You should be educated to a degree level as this course is catering for those seeking postgraduate academic credit. However, professionals who are involved with managing services and caseloads and have 5 years of work experience may also apply even if they do not hold a degree qualification.
Check whether your international qualifications meet our general entry requirements:
Before you apply for this course, you will need to complete a Byte Size Learning course (Introduction to Data Visualisation), which will provide an introduction to Data Visualisation: Knowlege Transfer.
Our Byte Size Learning is hosted on the Federation for Informatics Professionals in Health and Social Care (FEDIP) Hub. Introduction to Data Visualisation contains approximately an hour of content, and you will be able to apply for a CPD certificate upon completion.
To complete your Byte Size Learning, you will need to request access to the FEDIP Hub. Anyone can access the Hub for a 6-month trial for free, after which you must become FEDIP registered in order to maintain access. Request your free 6-month trial to the FEDIP Hub https://bit.ly/create_account_hub
You will be required to upload proof that you have completed this Byte Size course at the point of application for Data Visualisation: Knowledge Transfer.
You must be comfortable studying and learning in English if it is not your first language.
On completion of this course, the student will be able to:
- Demonstrate a critical understanding of modern data visualisation techniques and how to process the visual presentation of information.
- Apply knowledge and understanding to implement data visualisation through various media (interactive, infographic, story-telling) and design techniques (data physicalization, sketching, and paper prototypes) to solve specific real-world challenges and interpret data, and recognise their features and limitations.
- Apply critical analysis, evaluation, and synthesis to select the most appropriate technique for the visualisation challenge at hand, considering context, target audience, user accessibility, potential tasks that the visualisation should facilitate, and the data set's characteristics.
- Demonstrate the ability to effectively communicate challenges with end-users, stakeholders, peers, junior and senior colleagues using a range of data visualisation tools and why data visualisation is required.
- Critically reflect and evaluate their own and other's visualisation designs, make informed judgements and provide constructive solutions.
This is a 5-week course, comprising a total of 100 hours study.
( Lecture Hours 5, Seminar/Tutorial Hours 1, Online Activities 35, Feedback/Feedforward Hours 5, Formative Assessment Hours 5, Revision Session Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 46 )
Assessment is 100% coursework
At the start of a course, the students are sent a survey so that the sessions can be tailored to the majority of their availability, taking into account time zones, etc.
Funding
Course fees for 23/24 are £1065 but funded places may be available for people employed or unemployed in Scotland (residency requirements apply).
Through the Scottish Funding Council (SFC) Upskilling Fund, a limited number of fully-funded places are available on Data Upskilling Short Courses at The University of Edinburgh.
Eligibility
Funded places are available to those who meet SFC fee waiver criteria:
“Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.”
If you are from outside Scotland, you need to have settled status in the UK and meet other residency criteria:
- be ordinarily resident in the United Kingdom, the Channel Islands or the Isle of Man for the three years immediately before course start date, and
- have ‘settled status’ in the UK (as set out in the Immigration Act 1971) at the course start date, and
- be ordinarily resident in Scotland at the course start date.
You can find out more about residency criteria on the SAAS website or in this summary
Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. You can check your likely fee status here. Please email us at upskilling@ed.ac.uk if you would like to discuss your funding eligibility before applying.
Please note that full-time students (including full-time PhD students) are not eligible for funding.
You will receive a certificate of completion after the final assessment date if you have submitted your coursework.
Applications for April 2024 are now open.
Before you apply for this course, you will need to complete a Byte Size Learning course (Introduction to Data Visualisation), which will provide an introduction to Data Visualisation: Knowlege Transfer.
Our Byte Size Learning is hosted on the Federation for Informatics Professionals in Health and Social Care (FEDIP) Hub. Introduction to Data Visualisation contains approximately an hour of content, and you will be able to apply for a CPD certificate upon completion.
To complete your Byte Size Learning, you will need to request access to the FEDIP Hub. Anyone can access the Hub for a 6-month trial for free, after which you must become FEDIP registered in order to maintain access. Request your free 6-month trial to the FEDIP Hub https://bit.ly/create_account_hub
You will be required to upload proof that you have completed this Byte Size course at the point of application for Data Visualisation: Knowledge Transfer.
In order to verify that you meet the entry requirements for this course, you will be required to provide either:
- a degree certificate/transcript for your highest/most relevant academic qualification, or
- a CV and reference from an employer (if employed) or professional associate (if unemployed) outlining your suitability for the course
The degree certificate/transcript or CV should be emailed to upskilling@ed.ac.uk within 24 hours of submitting your application. References should be emailed to the same address (from an institutional/company account if from your employer) within 1 week of submitting your application.
Once complete, your application will be processed in 1-2 weeks. Applications will be processed on a first come, first served basis with priority given to applicants who meet the criteria for a funded place. We aim to email all applicants within 2 weeks of submission regardless of the outcome of their application.
Applications will close on 1st April 2024
You may also be able to use credits achieved on this course towards other University of Edinburgh postgraduate programmes, subject to the approval of the relevant Programme Director.
