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2022/23 Taught Postgraduate Programme Catalogue

MRes Data Science and Analytics for Health

Programme code:MOR-DS&AH-FTUCAS code:
Duration:12 Months Method of Attendance: Full Time
Programme manager:Owen Johnson Contact address:O.A.Johnson

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

Year1 - View timetable

[Learning Outcomes, Transferable (Key) Skills, Assessment]

Compulsory modules:

Students are required to study and pass the following compulsory modules:

COMP5122MData Science15 creditsSemester 1 (Sep to Jan)
COMP5513MWorkplace-based Data Science & Analytics Research and Development Project (Short Form)105 credits1 Feb to 31 Aug (19mth)
COMP5611MMachine Learning15 creditsSemester 2 (Jan to Jun)
COMP5712MProgramming for Data Science15 creditsSemester 1 (Sep to Jan)

Optional modules:

Candidates are required to study 30 credits from the following optional modules:

COMP5625MDeep Learning15 creditsSemester 2 (Jan to Jun)
COMP5840MData Mining and Text Analytics15 creditsSemester 2 (Jan to Jun)
LUBS5308MBusiness Analytics and Decision Science15 creditsSemester 1 (Sep to Jan)
LUBS5980MInnovation Management in Practice15 creditsSemester 2 (Jan to Jun)
MATH5743MStatistical Learning15 creditsSemester 2 (Jan to Jun)
MATH5820MBayesian Statistics and Causality15 creditsNot running in 202223
YCHI5075MSpatial Analytics and Visualisation for Health15 credits1 Apr to 30 June
YCHI5082MFoundations of Health Data15 credits01 Oct to 31 Dec
YCHI5083MHuman Factors in Health Data Science15 credits1 Mar to 30 Apr
YCHI5084MVisualisation for Health Data15 creditsNot running in 202223
YCHI5087MArtificial Intelligence and Machine Learning in Health15 creditsSemester 2 (Jan to Jun)

Non COMP modules subject to availability

Last updated: 22/09/2022 15:43:20


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