MEng Computer Science
Academic Year 2017/18
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 and Enhancement processes as set out in the DASA Policies and Procedures Manual.
Programme Title |
MEng Computer Science |
Final Award |
Master of Engineering |
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Programme Code |
CSC-MENG |
UCAS Code |
G402 |
JACS Code |
I100 (DESCR) 100 |
Criteria for Admissions A-level: AAB including Computing, Mathematics or Software Systems Development + GCSE Mathematics OR AAA including Chemistry, GCE A-level ICT (not Single Award Applied ICT), Physics, Technology or Double Award Applied ICT + GCSE Mathematics. |
ATAS Clearance Required |
No |
Health Check Required |
No |
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Portfolio Required |
Interview Required |
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Mode of Study |
Full Time |
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Type of Programme |
Undergraduate Master |
Length of Programme |
4 Academic Year(s) |
Total Credits for Programme |
480 |
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Exit Awards available |
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INSTITUTE INFORMATION
Awarding Institution/Body |
Queen's University Belfast |
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Teaching Institution |
Queen's University Belfast |
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School/Department |
Electronics, Electrical Engineering & Computer Sci |
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Framework for Higher Education Qualification Level |
Level 7 |
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QAA Benchmark Group |
Computing (2016) |
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Accreditations (PSRB) |
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British Computer Society (BCS) |
Date of most recent Accreditation Visit 17-10-13 |
REGULATION INFORMATION
Does the Programme have any approved exemptions from the University General Regulations None |
Programme Specific Regulations The programme is subject to the University General Regulations which can be found at: http://www.qub.ac.uk/directorates/AcademicStudentAffairs/AcademicAffairs/ |
Students with protected characteristics N/A |
Are students subject to Fitness to Practise Regulations (Please see General Regulations) No |
EDUCATIONAL AIMS OF PROGRAMME
The overall aim of the programme is to provide a broadly-based education in Computer Science, supported by fundamental topics in Software Engineering, which will produce graduates equipped to undertake research or apply best practice in software engineering. As an integrated Masters programme, students will have the opportunity to undertake advanced study within Computer Science.
• Embark on careers as professional Software Engineers or undertake research in Computer Science.
• Understand the fundamental principles of Computer Science and Software Engineering.
• Understand and able to use a range of current, emerging, novel and exciting developments in Computer Science theory and practice.
• Apply the skills necessary to critically evaluate new developments in Computer Science and take advantage of them where appropriate.
• Maintain a rigorous approach to the design and development of computing systems and the analysis of their correctness and complexity, which will remain applicable through changes in technology.
• Exercise high levels of professionalism and an awareness of the wider business and legal environment in which computer scientists operate.
• Possess strong interpersonal skills, encompassing team-working skills and effective oral, written, presentation and listening skills.
• Uphold the values, attitudes and competencies needed to undertake CPD and self-directed learning throughout their careers.
• Understand and be able to use a range of specialised and advanced topics in Software Engineering.
Consistent with the general Educational Aims of the Programme and the specific requirements of the Benchmarking Statement for Computing, 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 advantage of the learning opportunities that are provided.
Specifically, students graduating from the programme will have achieved the following learning outcomes, commensurate with degree classification, relating to subject specific knowledge and understanding; intellectual, practical and key transferable skills:
LEARNING OUTCOMES
Learning Outcomes: Cognitive SkillsOn the completion of this course successful students will be able to: |
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Analyse, evaluate and interpret information. |
Teaching/Learning Methods and Strategies All modules have a coursework component (practical Methods of Assessment Analysis and problem solving skills are assessed through homeworks, assignments and end-of-module written examinations. |
Synthesise information from a variety of sources |
Teaching/Learning Methods and Strategies All modules have a coursework component (practical Methods of Assessment Analysis and problem solving skills are assessed through homeworks, assignments and end-of-module written examinations. |
Evaluate designs, components, products and artefacts and make improvements. |
Teaching/Learning Methods and Strategies All modules have a coursework component (practical Methods of Assessment Analysis and problem solving skills are assessed through homeworks, assignments and end-of-module written examinations. |
Apply professional judgement to balance quality indicators in the design and construction of artefacts. |
Teaching/Learning Methods and Strategies All modules have a coursework component (practical Methods of Assessment Analysis and problem solving skills are assessed through homeworks, assignments and end-of-module written examinations. |
Recognise and analyse problems and develop strategies for their solution |
Teaching/Learning Methods and Strategies All modules have a coursework component (practical Methods of Assessment Analysis and problem solving skills are assessed through homeworks, assignments and end-of-module written examinations. |
Learning Outcomes: Knowledge & UnderstandingOn the completion of this course successful students will be able to: |
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Grasp the underpinning mathematics and theoretical framework of Computer Science |
Teaching/Learning Methods and Strategies Combination of lectures, tutorials, practical exercises and coursework in Levels 1 and 2. Methods of Assessment Unseen written examinations. Homework |
Apply the essential facts, concepts, principles and theories of Computer Science. |
Teaching/Learning Methods and Strategies Combination of lectures, tutorials, practical exercises, coursework and projects in Levels 2 and 3. Methods of Assessment Unseen written examinations, assessed practical work and homework. Project reports, presentations and demonstrations |
Adhere to good scientific and engineering practice in the specification, design, implementation, testing and delivery and maintenance of computer based solutions |
Teaching/Learning Methods and Strategies Combination of lectures, tutorials, practical exercises, coursework and projects in Levels 2 and 3. Methods of Assessment Unseen written examinations, assessed practical work and homework. Project reports, presentations and demonstrations |
Adhere to good scientific and engineering practice in the specification, design, implementation, testing and delivery and maintenance of computer based solutions |
Teaching/Learning Methods and Strategies Forms an integral part of all technical strands of the programme assuming increasing importance as students’ progress through the levels and is the dominant feature of final year technical modules. Methods of Assessment Unseen written examinations and assessed practical work Project reports, presentations and demonstration. |
Understand the importance of quality and fitness for purpose of the software engineering process and resulting artefacts |
Teaching/Learning Methods and Strategies Through lectures and projects in Levels 2 and 3. Methods of Assessment Unseen written examinations, project reports, presentations and demonstrations |
Maintain knowledge of the professional, legal and ethical responsibilities of Software Engineers and their role within an organisation. |
Teaching/Learning Methods and Strategies Through lectures in Level 2 and the Year of Professional Experience Methods of Assessment Unseen written examinations and assessed practical work, assignments and presentations |
Learning Outcomes: Subject SpecificOn the completion of this course successful students will be able to: |
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Plan and manage a Software Engineering project |
Teaching/Learning Methods and Strategies Taught in Level 2 and developed in the final year Methods of Assessment Subject specific practical skills are assessed through: coursework and technical reports and others forms of written project deliverable; code walkthroughs and analysis; and, project presentations and demonstrations. |
Implement a design using an appropriate programming language. |
Teaching/Learning Methods and Strategies Taught through lectures and supplemented through practical and project work. Methods of Assessment Subject specific practical skills are assessed through: coursework and technical reports and others forms of written project deliverable; code walkthroughs and analysis; and, project presentations and demonstrations. |
Deploy appropriate theory, practices and tools for the specification, design, |
Teaching/Learning Methods and Strategies Taught through lectures and developed through Methods of Assessment Subject specific practical skills are assessed through: coursework and technical reports and others forms of written project deliverable; code walkthroughs and analysis; and, project presentations and demonstrations. |
Deploy effectively the tools used in the construction and documentation of computer systems. |
Teaching/Learning Methods and Strategies Developed through practical and project work Methods of Assessment Subject specific practical skills are assessed through: coursework and technical reports and others forms of written project deliverable; code walkthroughs and analysis; and, project presentations and demonstrations. |
Prepare technical reports |
Teaching/Learning Methods and Strategies Developed through feedback on reports written for Methods of Assessment Subject specific practical skills are assessed through: coursework and technical reports and others forms of written project deliverable; code walkthroughs and analysis; and, project presentations and demonstrations. |
Give technical presentations. |
Teaching/Learning Methods and Strategies Developed through feedback on reports written for Methods of Assessment Subject specific practical skills are assessed through: coursework and technical reports and others forms of written project deliverable; code walkthroughs and analysis; and, project presentations and demonstrations. |
Learning Outcomes: Transferable SkillsOn the completion of this course successful students will be able to: |
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Work effectively within a team. |
Teaching/Learning Methods and Strategies Taught in Level 2 and developed through the Group Project module and in the various smaller group projects associated with other modules. Methods of Assessment Peer assessment |
Retrieve information from a variety of sources and by a variety of techniques |
Teaching/Learning Methods and Strategies Introduced during the University induction course and developed through assignments and project work involving library resources (catalogues), web-based resources (browsers and search engines) and personal contacts. Methods of Assessment Indirectly assessed |
Use information technology effectively. |
Teaching/Learning Methods and Strategies Developed through practical work, projects, assignments and other coursework activities and individual learning. Methods of Assessment Indirectly assessed |
Communicate effectively both verbally and in writing. |
Teaching/Learning Methods and Strategies Developed through assignments, homeworks, reports, presentations and demonstrations and developed through feedback on submitted coursework and presentations. Methods of Assessment Assessed through reports of practical work, assignments, homeworks, project reports, presentations and through the end of module examinations. |
Understand and present information involving a quantitative dimension. |
Teaching/Learning Methods and Strategies Taught through lectures, homeworks and practical work and developed through feedback on submitted coursework. Methods of Assessment Assessed through reports of practical work, assignments, homeworks, project reports, presentations and through the end of module examinations. |
Manage one’s own learning and development including time management and organisational skills. |
Teaching/Learning Methods and Strategies Taught in level 2. Students apply the skill in meeting Methods of Assessment Indirectly assessed |
Learn independently in familiar and unfamiliar situations with open-mindedness and a spirit of critical enquiry |
Teaching/Learning Methods and Strategies Nurtured and developed throughout the course which is structured and delivered in such a way as to promote this. Students apply and develop the skill during the Year of Professional Experience Methods of Assessment Indirectly assessed |
Plan and manage their career |
Teaching/Learning Methods and Strategies Developed through assignments Methods of Assessment Indirectly assessed |
Appreciate the need for continuing professional development in recognition of the need for lifelong learning. |
Teaching/Learning Methods and Strategies Promoted throughout the course Methods of Assessment Skill development |
MODULE INFORMATION
Programme Requirements
Module Title |
Module Code |
Level/ stage |
Credits |
Availability |
Duration |
Pre-requisite |
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Assessment |
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S1 | S2 | Core | Option | Coursework % | Practical % | Examination % | ||||||
Introduction to Software Engineering and Project Management | CSC1009 | 1 | 20 | YES | 12 weeks | N | YES | 100% | 0% | 0% | ||
Reasoning for Problem Solving | CSC1017 | 1 | 20 | YES | 12 weeks | N | YES | 60% | 40% | 0% | ||
Programming | CSC1020 | 1 | 40 | YES | YES | 24 weeks | N | YES | 50% | 0% | 50% | |
Architecture and Networks | CSC1022 | 1 | 20 | YES | 12 weeks | N | YES | 100% | 0% | 0% | ||
Databases | CSC1023 | 1 | 20 | YES | 12 weeks | N | YES | 30% | 30% | 40% | ||
Professional Computing Practice | CSC2011 | 2 | 10 | YES | YES | 24 weeks | N | YES | 85% | 15% | 0% | |
Architecture and Networks | CSC2039 | 2 | 10 | YES | 12 weeks | Y | YES | 60% | 0% | 40% | ||
Data Structures, Algorithms and Programming Languages | CSC2040 | 2 | 30 | YES | YES | 24 weeks | Y | YES | 30% | 30% | 40% | |
Information Modelling | CSC2042 | 2 | 10 | YES | 12 weeks | Y | YES | 50% | 50% | 0% | ||
Software Development - Processes and Practice | CSC2044 | 2 | 30 | YES | YES | 24 weeks | Y | YES | 100% | 0% | 0% | |
Theory of Computation | CSC2047 | 2 | 30 | YES | YES | 24 weeks | Y | YES | 60% | 0% | 40% | |
Concurrent Programming | CSC3021 | 3 | 20 | YES | 12 weeks | Y | YES | 50% | 50% | 0% | ||
Formal Methods | CSC3001 | 3 | 20 | YES | 12 weeks | Y | YES | 30% | 0% | 70% | ||
Agile & Component Based Development using .NET | CSC3045 | 3 | 20 | YES | 12 weeks | N | YES | 0% | 100% | 0% | ||
Software Testing | CSC3056 | 3 | 20 | YES | 12 weeks | N | YES | 60% | 0% | 40% | ||
Software Design Principles and Patterns | CSC3031 | 3 | 20 | YES | 12 weeks | N | YES | 15% | 15% | 70% | ||
Advanced Computer Architecture | CSC3058 | 3 | 20 | YES | 12 weeks | N | YES | 60% | 40% | 0% | ||
Malware Analysis | CSC3059 | 3 | 20 | YES | 12 weeks | N | YES | 0% | 40% | 60% | ||
Artificial Intelligence and Data Analytics | CSC3060 | 3 | 20 | YES | 12 weeks | N | YES | 40% | 60% | 0% | ||
Video Analytics and Machine Learning | CSC3061 | 3 | 20 | YES | 12 weeks | N | YES | 30% | 30% | 40% | ||
Data Analysis and Visualisation | CSC3062 | 3 | 20 | YES | 12 weeks | N | YES | 100% | 0% | 0% | ||
Secure Software Development | CSC3063 | 3 | 20 | YES | 12 weeks | N | YES | 30% | 30% | 40% | ||
Network Security | CSC3064 | 3 | 20 | YES | 12 weeks | N | YES | 40% | 20% | 40% | ||
Algorithms: Analysis and Application | CSC4003 | 4 | 20 | YES | 12 weeks | Y | YES | 30% | 0% | 70% | ||
Advanced Software Engineering | CSC4002 | 4 | 20 | YES | 12 weeks | N | YES | 100% | 0% | 0% | ||
High Performance Computing: Principles of Parallel Programming | CSC4005 | 4 | 20 | YES | 12 weeks | N | YES | 0% | 100% | 0% | ||
Research and Development Project | CSC4006 | 4 | 40 | YES | YES | 24 weeks | N | YES | 100% | 0% | 0% | |
Advanced Machine Learning | CSC4007 | 4 | 20 | YES | 12 weeks | N | YES | 60% | 0% | 40% |
Notes