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Postgraduate Programme Specification

PgCert Biostatistics and Bioinformatics

Academic Year 2022/23

A programme specification is required for any programme on which a student may be registered. All programmes of the University are subject to the University's Quality Assurance processes. All degrees are awarded by Queen's University Belfast.

Programme Title PgCert Biostatistics and Bioinformatics Final Award
(exit route if applicable for Postgraduate Taught Programmes)
Postgraduate Certificate
Programme Code MED-PC-BB UCAS Code HECoS Code 100869 - Bioinformatics - 100

ATAS Clearance Required

No

Health Check Required

No

Portfolio Required

--

Interview Required

--

Mode of Study Part Time
Type of Programme Postgraduate Length of Programme Part Time - 1 Academic Year
Total Credits for Programme 60
Exit Awards available No

Institute Information

Teaching Institution

Queen's University Belfast

School/Department

Medicine, Dentistry and Biomedical Sciences

Quality Code
https://www.qaa.ac.uk/quality-code

Higher Education Credit Framework for England
https://www.qaa.ac.uk/quality-code/higher-education-credit-framework-for-england

Level 7

Subject Benchmark Statements
https://www.qaa.ac.uk/quality-code/subject-benchmark-statements

The Frameworks for Higher Education Qualifications of UK Degree-Awarding Bodies
https://www.qaa.ac.uk/docs/qaa/quality-code/qualifications-frameworks.pdf

N/A

Accreditations (PSRB)

No accreditations (PSRB) found.

Regulation Information

Does the Programme have any approved exemptions from the University General Regulations
(Please see General Regulations)

No

Programme Specific Regulations

AWARDS, CREDITS AND PROGRESSION OF LEARNING OUTCOMES

The following regulations should be read in conjunction with the General Regulations of the University.

Students must pass all modules (60CATS) to be awarded the Certificate

Students with protected characteristics

N/A

Are students subject to Fitness to Practise Regulations

(Please see General Regulations)

No

Educational Aims Of Programme

The aim of the programme is to provide a strong foundation in biostatistics and bioinformatics.

Essential domain knowledge and context will be provided via an introduction to cell biology.

Students will gain key, transferable, statistical, data analytical and scripting skills which will, in turn, provide a springboard into further specialist bioinformatics training and qualifications.

Learning Outcomes

Learning Outcomes: Cognitive Skills

On the completion of this course successful students will be able to:

Critically evaluate scientific literature.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Creatively apply and extend scientific principles to new problems.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Efficiently analyse and summarise core concepts from diverse sources.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Learning Outcomes: Transferable Skills

On the completion of this course successful students will be able to:

Critical, analytical and creative thinking.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Oral communication and in writing scientific documentation

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Handling various types of IT resources.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Time management

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Team work

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Learning Outcomes: Knowledge & Understanding

On the completion of this course successful students will be able to:

Communicate the principles of cell biology.

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Perform statistical analyses and interpret the output from such analyses

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Explain basic principles of statistical methods.

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Utilise the basic elements of programming languages such as R

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Communicate the importance of data integration

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Explain the key concepts in health informatics and its integration with translational bioinformatics to facilitate the development of precision medicine approaches

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Learning Outcomes: Subject Specific

On the completion of this course successful students will be able to:

Select, apply and interpret statistical methods in the analysis of biomedical, omics and clinical data

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Interrogate relevant online resources for efficient data retrieval and analysis

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Utilise comprehensive programming skills.

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Utilise a variety of existing databases in biomedical research

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Module Information

Stages and Modules

Module Title Module Code Level/ stage Credits

Availability

Duration Pre-requisite

Assessment

S1 S2 Core Option Coursework % Practical % Examination %
Introductory Cell Biology & Computational analysis for Bioinformatics SCM8159 7 10 -- YES 6 weeks N YES -- 100% 0% 0%
Biostatistical Informatics SCM8109 7 20 -- YES 12 weeks N YES -- 100% 0% 0%
Health and Biomedical informatics and the exposome SCM8148 7 10 -- YES 6 weeks N YES -- 100% 0% 0%
Scientific Programming & Statistical Computing SCM7047 7 20 YES YES 12 weeks N YES -- 100% 0% 0%

Notes

No notes found.