Name of Programme
MSc Applied Computing
Final Award
MSc
Location
³Ô¹ÏÍø
Awarding Institution/Body
University Of ³Ô¹ÏÍø
Teaching Institution
University Of ³Ô¹ÏÍø
School of Study
School of Computing
Programme Code(s)
PMSF1PAP / Full Time / 1.5 Years
Professional Body Accreditation
N/A
Relevant Subject Benchmark Statement (SBS)
QAA Computing (2022)
Admission Criteria
2:2 BSc (Hons) Computing
IELTS 6.5
Applicable Cohort(s)
September 2023
FHEQ Level
7
UCAS Code
Summary of Programme
This programme is a specialised advanced master’s programme for first degree holders in computing related areas such as computer science, computer engineering and software engineering. Suitable candidates from backgrounds in business computing and information systems may also be admitted. The programme is fundamentally the same as the MSc Innovative Computing programme. The prolonged period of study provides students of a wider range of backgrounds with more time and space to consolidate their understanding and develop their specialised skills.
Educational Aims of the Programme
In the current competitive IT job market, in-depth knowledge in specialised subject areas of applied computing is increasingly in demand. This degree programme is designed to meet such needs of the market. Based on the research strengths and expertise at the School of Computing and appointed visiting professors and fellows from IT industry and research, this degree programme provides pathways into specialised subject areas of computing such as artificial intelligence, applied computer vision and machine learning, robotics information security in communication, data mining solutions for enterprises and web technologies.

The graduates of the programme should be equipped with the specialised subject knowledge, enhanced technical skills, and independence further developed from their individual project experience. They should be able to compete with graduates of master’s programmes from other UK universities. The programme also builds a strong foundation for those students who want to pursue higher degrees by research either in University of ³Ô¹ÏÍø or elsewhere in the UK, or in universities abroad.

Programme Outcomes

Knowledge and Understanding

At the end of the programme students should be able to gain knowledge and understanding in:
1. The role that computers systems now play in the modern society
2. A range of modern computing techniques together with relevant skills to apply the techniques in practice
3. The state-of-art development of specialised areas of computing technology and its applications
4. Critical evaluation of existing and new solutions and their limitation in a chosen area of computing technology

Teaching/Learning Strategy

The ILOs are achieved through a mixture of lectures, workshops/seminars, tutorial classes and practical classes. Individual study and self-reliance on the learning side are expected for such an advanced master’s programme:
1. Seminars and presentations
2. Lectures, Tutorial Practical exercises
3. Lectures, individual project and research as a part of coursework
4. Individual project and coursework

Assessment Strategy

Assessment of the ILOs is through the following means where numbers in the brackets refer to the ILO items:
- Exams (1, 3)
- Coursework (1, 2, 3, 4)
- Practical exams & tests (2).
- Project reports (1, 3, 4)
- Project presentation (1, 3, 4)
- Project software (1, 3)
- Project viva (1, 2, 3, 4)
Programme Outcomes

Cognitive Skills

At the end of the programme students should be able to gain:
1. Problem solving skills
2. Research skills
3. Analysis and evaluation skills
4. Communication and teamwork kills

Teaching/Learning Strategy

For all the cognitive skills listed:
• A Research Methods training course is offered
• Coursework/team projects and individual project both provide opportunity for practising the skills

Assessment Strategy

All the cognitive skills listed are assessed by the following means:
- Coursework
- Practical examinations
- Project reports
- Project viva
Programme Outcomes

Practical/Transferable Skills

At the end of the programme students should be able to:
1. General technical skills in a range of computing technologies within the scope of the programme
2. Advanced technical skills in a chosen area of computing technology within the scope of the programme
3. Software development & practical use skills
4. Programming and fast prototyping skills
5. Project management skills
6. Communication Skills
7. Self-learning and individual study skills
8. Presentation skills
9. Teamwork skills

Teaching/Learning Strategy

The skills are obtained through practice in:
1. Coursework and practical classes
2. Individual project
3. Individual project
4. Individual project
5. Individual project and course project
6. Coursework and course projects
7. Oral presentations
8. Project Demonstrations
9. Group course projects

Assessment Strategy

The key skills are assessed by the following means where numbers in the brackets refer to the corresponding skills:
- Coursework and written/practical examinations (all)
- Project reports and viva (6,7,8)
- Written essays and reports (6,7,8)
- Oral presentation performance (6,7,8)
- Demonstration performance (6,8)
- Group module projects demonstrations (9)
External Reference Points
• Framework for Higher Education Qualifications ();
• Relevant Subject Benchmark Statement(s) ();

Please note: This specification provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are provided. More detailed information on the learning outcomes, content and teaching, learning and assessment methods of each course unit/module can be found in the departmental or programme handbook. The accuracy of the information contained in this document is reviewed annually by the University of ³Ô¹ÏÍø and may be checked by the Quality Assurance Agency.
Date of Production
January 2012
Date approved by School Learning and Teaching Committee
Latest Revision: November 2023
Date approved by School Board of Study
Latest Revision: November 2023
Date approved by University Learning and Teaching Committee
Latest Revision: November 2023
Date of Annual Review
In line with the University annual monitoring review process

 

PROGRAMME STRUCTURES

MSc Applied Computing

PMSF1PAP / Full Time / April Entry
Term 1
Spring
Web Technologies and Applications [L7/15U] (SPFWTAA)
Applied Computer Vision and Machine Learning [L7/15U] (SPFCVML)
June Examination
Term 2
Summer
Robotics [L7/15U] (SPFROBO)
One of:
Dissertation [L7/15U]
Work Placement [L7/15U] (FCLP9) ***
Term 3
Autumn
Research Methods [L7/15U] (SPFRMET)
One of:
Cloud Computing [L6/15U]
Digital Forensics and Cyber Incident Management [L6/15U] (FCLP8) **
December Examination
Term 4
Winter
Information Security in Communication [L7/15U] (SPFISCM)
Artificial Intelligence In Practice [L7/15U] (SPFAINT)
Individual Project Applied Computing [L7/60U] (SPFPRAC)
Term 5
Spring
Applied Techniques of Data Mining and Machine Learning [L7/15U] (SPFDMML) *
Individual Project Applied Computing [L7/60U] (SPFPRAC)
(Continued)
June(2) Examination
Term 6
Summer
Individual Project Applied Computing [L7/60U] (SPFPRAC)
(Continued)
Project

*** Work Placement is offered on the basis of available opportunity. Students are required to look for work placement opportunities themselves. In the extremely rare cases where work placement opportunities cannot be located, the students are required to complete a 15-unit dissertation (see the Dissertation module specification for more details).
** Students can choose a level 6 module of their own interest in the Autumn or Summer Term, this would have an influence on the start term of the project
* Please note there are Special Regulations governing this programme, which can be reviewed in the University of ³Ô¹ÏÍø’s regulations Handbook: /about/handbooks/regulations-handbook

 

MSc Applied Computing

PMSF1PAP / Full Time / January Entry
Term 1
Winter
Artificial Intelligence In Practice [L7/15U] (SPFAINT)
Research Methods [L7/15U] (SPFRMET)
Term 2
Spring
Web Technologies and Applications [L7/15U] (SPFWTAA)
Applied Computer Vision and Machine Learning [L7/15U] (SPFCVML)
June Examination
Term 3
Summer
Robotics [L7/15U] (SPFROBO)
Individual Project Applied Computing [L7/60U] (SPFPAC3) *
Term 4
Autumn
One of:
Cloud Computing [L6/15U]
Digital Forensics and Cyber Incident Management [L6/15U] (FCLP8) **
Individual Project Applied Computing [L7/60U] (SPFPAC3) *
(Continued)
December Examination
Term 5
Winter
Information Security in Communication [L7/15U] (SPFISCM)
Individual Project Applied Computing [L7/60U] (SPFPAC3) *
(Continued)
One of:
Dissertation [L7/15U]
Work Placement [L7/15U] (FCLP9) ***
Term 6
Spring
Applied Techniques of Data Mining and Machine Learning [L7/15U] (SPFDMML)
Individual Project Applied Computing [L7/60U] (SPFPAC3) *
(Continued)
June (2) Examination

* Please note there are Special Regulations governing this programme, which can be reviewed in the University of ³Ô¹ÏÍø’s regulations Handbook: /about/handbooks/regulations-handbook/
** Students can choose a level 6 module of their own interest in the Autumn or Summer Term, this would have an influence on the start term of the project
*** Work Placement is offered on the basis of available opportunity. Students are required to look for work placement opportunities themselves. In the extremely rare cases where work placement opportunities cannot be located, the students are required to complete a 15-unit dissertation (see the Dissertation module specification for more details).

 

MSc Applied Computing

PMSF1PAP / Full Time / September Entry
Term 1
Autumn
Research Methods [L7/15U] (SPFRMET)
One of:
Cloud Computing [L6/15U]
Digital Forensics and Cyber Incident Management [L6/15U] (FCLP8)
December Examination
Term 2
Winter
Artificial Intelligence In Practice [L7/15U] (SPFAINT)
Information Security in Communication [L7/15U] (SPFISCM)
Term 3
Spring
Web Technologies and Applications [L7/15U] (SPFWTAA)
Applied Computer Vision and Machine Learning [L7/15U] (SPFCVML)
Applied Techniques of Data Mining and Machine Learning [L7/15U] (SPFDMML)
June Examination
Term 4
Summer
Robotics [L7/15U] (SPFROBO)
Individual Project Applied Computing [L7/60U] (SPFPRAC) *
Term 5
Autumn
One of:
Dissertation [L7/15U]
Work Placement [L7/15U] (FCLP9) **
Individual Project Applied Computing [L7/60U] (SPFPRAC) *
(Continued)
Term 6
Winter
Individual Project Applied Computing [L7/60U] (SPFPRAC) *
(Continued)
December (2) Examination

* Individual Project: A pass in the project is a requirement for the award of a degree. The degree will not normally be awarded a higher classification than that awarded to the project.
** Work Placement is offered on the basis of available opportunity. Students are required to look for work placement opportunities themselves. In the extremely rare cases where work placement opportunities cannot be located, the students are required to complete a 15-unit dissertation (see the Dissertation module specification for more details).