2020/21 Taught Postgraduate Programme Catalogue
MRes Data Science and Analytics for Health
Programme code: | MOR-DS&AH-FT | UCAS code: | |
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Duration: | 12 Months | Method of Attendance: | Full Time |
Total credits: 180
Entry requirements:
School/Unit responsible for the parenting of students and programme:
School of Computing
Examination board through which the programme will be considered:
School of Computing
Programme specification:
The programme provides a comprehensive training in the management, modelling and interpretation of the
increasing amounts of health and healthcare data that are becoming available from a diverse range of clinical,
behavioural and organisational sources - skills that will enable students to extract valuable empirical evidence to
better understand the causes of disease, and more accurately predict and evaluate health outcomes and health
service needs.
The programme draws on recent advances in information technology, data management, statistical modelling (for
description/classification, causal inference and prediction), machine learning and artificial intelligence. It intends
to equip health data scientists and health data analysts with the skills required to: harness the empirical insights
available within large and varied data sources; and apply these to pressing clinical, social and organisational
questions within the broad and varied context of health and healthcare services.
The programme is designed to enable students to develop both the technical and applied skills required for
addressing real-world challenges in real-world health and healthcare contexts.
A distinctive feature of the programme is the inclusion of extended periods of hands-on data science practice
working on applied and collaborative workplace-based projects across a range of health and healthcare
services under the co-supervision of service-specific specialists and academic experts in the management,
analysis and interpretation of health and healthcare data. These projects offer students opportunities to:
apply, test and further refine the skills the MRes will provide in data science and analytics; experience working
within established data science teams addressing pressing and pertinent health and healthcare problems;
develop invaluable transferable skills relevant to interdisciplinary team science; and generate analytical tools,
empirical findings, and evidence-based insights with the potential to have tangible impacts on health and
healthcare policy and practice.
The programme draws together: (i) established expertise in applied data science relevant to the statistical
modelling of complex data and the use of machine learning and artificial intelligence to accelerate the
application of modelling for insight and discovery through causal inference and prediction; and (ii) key public
and private sector partners with extensive experience of managing a range of complex health and healthcare
data sources, and harnessing these to inform professional practice, service delivery, public policy and
commercialisation.
Year1 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Students are required to study and pass the following compulsory modules:
Compulsory modules:
COMP5510M | Data Science & Analytics for Causal Inference and Prediction | 15 credits | 1 Sep to 31 Jan (adv yr), Semester 1 (Sep to Jan) | |
COMP5511M | Principles of Data Science & Analytics | 15 credits | 1 Sep to 31 Jan (adv yr), Semester 1 (Sep to Jan) | |
COMP5611M | Machine Learning | 15 credits | Semester 1 (Sep to Jan), 1 Sep to 31 Jan (adv yr) | |
COMP5623M | Artificial Intelligence | 15 credits | Semester 2 (Jan to Jun) |
Optional modules:
If you opted to study COMP5513M Workplace-based Data Science & Analytics Research and Development Project - (short form 105 credits) you are also required to study and pass COMP5712M Programming for Data Science (15 credits).
If you did NOT opt to study COMP5513M you are required to study and pass COMP5512M Workplace-based Data Science & Analytics Research and Development Project (Long Form - 120 credits).
COMP5512M | Workplace-based Data Science & Analytics Research and Development Project (Long Form) | 120 credits | 1 Feb to 31 Aug (19mth) | |
COMP5513M | Workplace-based Data Science & Analytics Research and Development Project (Short Form) | 105 credits | 1 Feb to 31 Aug (19mth) | |
COMP5712M | Programming for Data Science | 15 credits | 1 Jan to 31 May, Semester 1 (Sep to Jan), 1 Jun to 30 Sep, 1 Sep to 31 Jan (adv yr) |
Last updated: 16/10/2020 10:15:16
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