Undergraduate Programme Specification
MSci Mathematics and Computer Science
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 | MSci Mathematics and Computer Science | Final Award (exit route if applicable for Postgraduate Taught Programmes) |
Master in Science | |||||||||||
| Programme Code | MTH-MSCI | UCAS Code | GGK1 | HECoS Code |
100366 - Computer science - 33 100403 - Mathematics - 67 |
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| ATAS Clearance Required | No | |||||||||||||
| Mode of Study | Full Time | |||||||||||||
| Type of Programme | Undergraduate Master | Length of Programme |
Full Time - 4 Academic Years |
Total Credits for Programme | 480 | |||||||||
| Exit Awards available | No | |||||||||||||
Institute Information
Teaching Institution |
Queen's University Belfast |
School/Department |
Mathematics & Physics |
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Quality Code Higher Education Credit Framework for England |
Level 7 |
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Subject Benchmark Statements The Frameworks for Higher Education Qualifications of UK Degree-Awarding Bodies |
Mathematics, Statistics and Operational Research (2019) |
Accreditations (PSRB) |
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Institute of Mathematics and its Applications |
Date of most recent Accreditation Visit 04-06-13 |
Regulation Information
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Does the Programme have any approved exemptions from the University General Regulations No |
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Programme Specific Regulations Students will not be permitted to register for Stage 2 unless they have passed all their core Level 1 modules. |
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Students with protected characteristics N/A |
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Are students subject to Fitness to Practise Regulations (Please see General Regulations) No |
Educational Aims Of Programme
-Demonstrate good understanding of the main body of knowledge for mathematics, including some advanced topics, and demonstrate good skill in manipulation of this knowledge, including in its application to problem solving
-Apply core mathematics concepts in loosely defined contexts, through the judicious use of analytical and computational methods, tools and techniques and high-level skills in the development and evaluation of logical mathematical arguments
-Analyse problems through their formulation in terms of mathematics
-Communicate mathematical and computer science arguments to a range of audiences in both written and oral form
-Embark on careers as professional computer scientists and/or mathematicians, including research careers
-Develop sound engineering practice in the approach to system design and development, including the adoption of and adaptation to new technologies
Learning Outcomes
Learning Outcomes: Cognitive SkillsOn the completion of this course successful students will be able to: |
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Apply mathematical knowledge logically and accurately in the solution of examples and complex problems |
Teaching/Learning Methods and Strategies By its nature, mathematics has to be presented logically. The lectures and model examples to problems provide exemplars of this logical structure. They also identify the tools needed to address certain problems. Tutorial problems and assignments offer the students opportunities to develop their logical reasoning skills, to develop skills in organising their reasoning and application of mathematics, and to develop skills in the selection of techniques. Methods of Assessment The assessment of these skills is implicit in most methods of assessment, including exams, coursework, practical and project work. The overall degree of success in any assessment depends to a large extent on students’ mastery of logical and accurate methods of solution, well-organised structure of answers, and the identification of the appropriate solution method. |
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Conduct an advanced mathematical investigation under supervision |
Teaching/Learning Methods and Strategies The project modules will offer the students the opportunity to identify what it takes to carry out an extended, advanced investigation in pure or applied mathematics. These skills are also developed through extended assignments in a wide range of modules across the entire spectrum Methods of Assessment These skills are assessed mainly through project reports and oral presentations on project work of increasing complexity, culminating in the final project |
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Analyse complex problems and situations in mathematical terms, and identify the appropriate mathematical tools and techniques for their solution |
Teaching/Learning Methods and Strategies By its nature, mathematics has to be presented logically. The lectures and model examples to problems provide exemplars of this logical structure. They also identify the tools needed to address certain problems. Tutorial problems and assignments offer the students opportunities to develop their logical reasoning skills, to develop skills in organising their reasoning and application of mathematics, and to develop skills in the selection of techniques. Methods of Assessment The assessment of these skills is implicit in most methods of assessment, including exams, coursework, practical and project work. The overall degree of success in any assessment depends to a large extent on students’ mastery of logical and accurate methods of solution, well-organised structure of answers, and the identification of the appropriate solution method. |
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Organise their work in a structured manner |
Teaching/Learning Methods and Strategies By its nature, mathematics has to be presented logically. The lectures and model examples to problems provide exemplars of this logical structure. They also identify the tools needed to address certain problems. Tutorial problems and assignments offer the students opportunities to develop their logical reasoning skills, to develop skills in organising their reasoning and application of mathematics, and to develop skills in the selection of techniques. Methods of Assessment The assessment of these skills is implicit in most methods of assessment, including exams, coursework, practical and project work. The overall degree of success in any assessment depends to a large extent on students’ mastery of logical and accurate methods of solution, well-organised structure of answers, and the identification of the appropriate solution method. |
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Evaluate software designs, components, products and artefacts and make improvements |
Teaching/Learning Methods and Strategies All Computer Science modules have a coursework component (practical work, homework or assignments) which supports, illustrates and reinforces the theoretical material presented in lectures Methods of Assessment Analysis and problem solving skills are assessed through homework, assignments and end-of-module written examinations. Design skills are assessed through assignments, reports on practical work and project reports, presentations and demonstrations. |
Learning Outcomes: Knowledge & UnderstandingOn the completion of this course successful students will be able to: |
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Demonstrate understanding of the fundamental concepts and techniques of calculus, analysis, algebra, linear algebra and numerical methods |
Teaching/Learning Methods and Strategies Lectures provide the core method for the presentation of the knowledge required for students to be successful. Each lecture-based module has associated tutorials, and, where appropriate, practical classes to assist the student with the development of understanding of the core contents, including its application. Assignments are provided to assist further development of understanding. These assignments are marked and returned to students typically within one week with individual feedback. Model solutions to these assignments are made available to students for additional self-study. Methods of Assessment Formal exams, class tests, small reports, presentations |
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Use these fundamental concepts and techniques in a range of application areas, including, for example, partial differential equations, mechanics, numerical analysis, statistics and operational research |
Teaching/Learning Methods and Strategies Lectures provide the core method for the presentation of the knowledge required for students to be successful. Each lecture-based module has associated tutorials, and, where appropriate, practical classes to assist the student with the development of understanding of the core contents, including its application. Assignments are provided to assist further development of understanding. These assignments are marked and returned to students typically within one week with individual feedback. Model solutions to these assignments are made available to students for additional self-study. Methods of Assessment Formal exams, class tests, small reports, presentations |
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Understand and appreciate the importance of mathematical logic |
Teaching/Learning Methods and Strategies Lectures provide the core method for the presentation of the knowledge required for students to be successful. Each lecture-based module has associated tutorials, and, where appropriate, practical classes to assist the student with the development of understanding of the core contents, including its application. Assignments are provided to assist further development of understanding. These assignments are marked and returned to students typically within one week with individual feedback. Model solutions to these assignments are made available to students for additional self-study. Methods of Assessment Formal exams, class tests, small reports, presentations |
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Demonstrate understanding, and application of this understanding, within a range of more specialist optional topics, including some advanced topics |
Teaching/Learning Methods and Strategies Lectures provide the core method for the presentation of the knowledge required for students to be successful. Each lecture-based module has associated tutorials, and, where appropriate, practical classes to assist the student with the development of understanding of the core contents, including its application. Assignments are provided to assist further development of understanding. These assignments are marked and returned to students typically within one week with individual feedback. Model solutions to these assignments are made available to students for additional self-study. Methods of Assessment Formal exams, class tests, small reports, presentations |
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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. Acquisition of (c) is through a combination of lectures, tutorials, practical exercises, coursework and projects at all levels. Methods of Assessment Unseen written examinations and assessed practical work Project reports, presentations and demonstration. |
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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 |
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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 Methods of Assessment Unseen written examinations and assessed practical work, assignment |
Learning Outcomes: Subject SpecificOn the completion of this course successful students will be able to: |
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Demonstrate understanding of logical mathematical arguments, including mathematical proofs and their construction, and apply these arguments appropriately |
Teaching/Learning Methods and Strategies Each lecture-based module has associated tutorials, and, where appropriate, practical classes to assist the student with the development of understanding and application of logical mathematical arguments and/or analytic/numerical mathematical techniques. Assignments also assist the development of understanding in these areas. Methods of Assessment Assessment is mainly through formal examination and class tests for lecture-based modules. This assessment is supplemented through written reports and oral presentations. For project modules, the latter is the main method of assessment. |
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Apply a wide range of analytic and/or numerical mathematical techniques within well-defined contexts, and to formulate and solve problems in more loosely defined contexts |
Teaching/Learning Methods and Strategies Each lecture-based module has associated tutorials, and, where appropriate, practical classes to assist the student with the development of understanding and application of logical mathematical arguments and/or analytic/numerical mathematical techniques. Assignments also assist the development of understanding in these areas. Methods of Assessment Assessment is mainly through formal examination and class tests for lecture-based modules. This assessment is supplemented through written reports and oral presentations. For project modules, the latter is the main method of assessment. |
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Use a range of mathematical software for the solution of mathematical problems |
Teaching/Learning Methods and Strategies Basic skills are developed through the mathematical modelling module and the computer algebra module. Numerical analysis and statistics oriented modules have associated computer practical, using appropriate specialist software. Methods of Assessment These skills are primarily assessed through reports and presentations associated with work carried out using mathematical software. |
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Present mathematical findings accurately through oral and written means to a range of audiences |
Teaching/Learning Methods and Strategies Communication through reports and/or oral presentations forms a compulsory part of many modules across the entire range of modules offered. Methods of Assessment These skills are primarily assessed through compulsory reports and presentations within many modules. |
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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 Practical skills are assessed through reports on practical work, coursework reports and presentations |
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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 Practical skills are assessed through reports on practical work, coursework reports and presentations |
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Deploy appropriate theory, practices and tools for the specification, design, implementation and evaluation of computer based systems |
Teaching/Learning Methods and Strategies Taught through lectures and developed through homework, assignments, practical and project work Methods of Assessment Practical skills are assessed through reports on practical work, coursework reports and presentations |
Learning Outcomes: Transferable SkillsOn the completion of this course successful students will be able to: |
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Adopt an analytic approach to problem solving |
Teaching/Learning Methods and Strategies Analytic thinking is part of any module in mathematics, and is therefore cultivated through the tutorials, practical and assignments associated with each lecture-based module, including all the project components. Methods of Assessment Analytic thinking is embedded implicitly in every assessment within mathematics. |
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Use computer technology efficiently for a variety of purposes |
Teaching/Learning Methods and Strategies Developed primarily within computer science through practical work, projects, assignments and other coursework activities and individual learning Methods of Assessment Assessed through practical work, projects, assignments and other coursework activities and individual learning |
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Communicate mathematical ideas and concepts accurately and Present findings through written reports |
Teaching/Learning Methods and Strategies Any assignment or coursework or project work involves the communication of mathematical ideas, and these skills are thus embedded indirectly in any module. Methods of Assessment The assessment of communication skills takes place through the reports and presentations, where higher skill levels will result in higher overall marks |
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Present findings through oral communication |
Teaching/Learning Methods and Strategies Any assignment or coursework or project work involves the communication of mathematical ideas, and these skills are thus embedded indirectly in any module. Methods of Assessment The assessment of communication skills takes place through the reports and presentations, where higher skill levels will result in higher overall marks |
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Manage their time |
Teaching/Learning Methods and Strategies Project work associated with modules at each Level are the prime method for development. The increase in level of complexity of such projects throughout the programme, in line with student’s overall development, will implicitly develop the students’ skills in project management. Methods of Assessment These skills are assessed implicitly as part of any project component to a module. A higher level of skill in time management will provide student with greater opportunity to present a well thought-through report, which allows the students to better highlight their achievements.The assessment of communication skills takes place through the reports and presentations, where higher skill levels will result in higher overall marks |
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Oversee extended projects |
Teaching/Learning Methods and Strategies Project work associated with modules at each Level are the prime method for development. The increase in level of complexity of such projects throughout the programme, in line with student’s overall development, will implicitly develop the students’ skills in project management. Methods of Assessment These skills are assessed implicitly as part of any project component to a module. A higher level of skill in time management will provide student with greater opportunity to present a well thought-through report, which allows the students to better highlight their achievements. |
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Appreciate the need for continuous professional development in recognition for the need of lifelong learning |
Teaching/Learning Methods and Strategies Promoted throughout Computer Science modules Methods of Assessment Assessed through the development of skills |
Module Information
Stages and Modules
| Module Title | Module Code | Level/ stage | Credits | Availability |
Duration | Pre-requisite | Assessment |
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| S1 | S2 | Core | Option | Coursework % | Practical % | Examination % | ||||||
| Algorithmic Thinking | MTH1025 | 1 | 10 | -- | YES | 12 weeks | N | YES | -- | 100% | 0% | 0% |
| Object Oriented Programming | CSC1029 | 1 | 20 | -- | YES | 12 weeks | N | YES | -- | 50% | 30% | 20% |
| Introduction to Algebra and Analysis | MTH1011 | 1 | 30 | YES | YES | 24 weeks | N | YES | -- | 0% | 0% | 100% |
| Mathematical Reasoning | MTH1015 | 1 | 10 | YES | -- | 12 weeks | N | YES | -- | 65% | 35% | 0% |
| Mathematical Methods 1 | MTH1021 | 1 | 30 | YES | YES | 24 weeks | N | YES | -- | 15% | 0% | 85% |
| Procedural Programming | CSC1025 | 1 | 20 | YES | -- | 12 weeks | N | YES | -- | 60% | 40% | 0% |
| Mathematical Methods 2 | MTH2021 | 2 | 20 | -- | YES | 12 weeks | Y | -- | YES | 40% | 0% | 60% |
| Professional and Transferrable Skills | CSC2065 | 2 | 20 | YES | -- | 12 weeks | N | -- | YES | 100% | 0% | 0% |
| Analysis | MTH2012 | 2 | 20 | YES | -- | 12 weeks | Y | -- | YES | 10% | 0% | 90% |
| Linear Algebra | MTH2011 | 2 | 20 | YES | -- | 12 weeks | Y | YES | -- | 30% | 0% | 70% |
| Employability for Mathematics | MTH2010 | 2 | 0 | YES | -- | 12 weeks | N | -- | YES | 100% | 0% | 0% |
| Theory of Computation | CSC2060 | 2 | 20 | -- | YES | 12 weeks | N | -- | YES | 40% | 0% | 60% |
| Metric Spaces | MTH2013 | 2 | 20 | -- | YES | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Classical Mechanics | MTH2031 | 2 | 20 | YES | -- | 12 weeks | Y | -- | YES | 20% | 0% | 80% |
| Group Theory | MTH2014 | 2 | 20 | -- | YES | 12 weeks | Y | -- | YES | 30% | 0% | 70% |
| Introduction to Artificial Intelligence and Machine Learning | CSC2062 | 2 | 20 | -- | YES | 12 weeks | N | -- | YES | 60% | 0% | 40% |
| Data Structures and Algorithms | CSC2059 | 2 | 20 | YES | -- | 12 weeks | N | YES | -- | 50% | 50% | 0% |
| Classical Fields | MTH3031 | 3 | 20 | YES | -- | 12 weeks | Y | -- | YES | 30% | 0% | 70% |
| Numerical Analysis | MTH3023 | 3 | 20 | YES | -- | 12 weeks | Y | -- | YES | 50% | 0% | 50% |
| Rings and Modules | MTH3012 | 3 | 20 | YES | -- | 12 weeks | Y | -- | YES | 30% | 0% | 70% |
| Discrete Mathematics | MTH3022 | 3 | 20 | -- | YES | 12 weeks | Y | -- | YES | 30% | 0% | 70% |
| Fourier Analysis and Applications to PDEs | MTH4321 | 3 | 20 | -- | YES | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Dynamical Systems | MTH3021 | 3 | 20 | -- | YES | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Measure and Integration | MTH3011 | 3 | 20 | YES | -- | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Formal Methods | CSC3001 | 3 | 20 | -- | YES | 12 weeks | Y | -- | YES | 30% | 0% | 70% |
| Deep Learning | CSC3066 | 3 | 20 | -- | YES | 12 weeks | N | -- | YES | 60% | 0% | 40% |
| Video Analytics and Machine Learning | CSC3067 | 3 | 20 | YES | -- | 12 weeks | N | -- | YES | 40% | 0% | 60% |
| Mathematical Investigations | PMA3013 | 3 | 20 | -- | YES | 12 weeks | N | YES | -- | 90% | 10% | 0% |
| Modelling and Simulation | MTH3024 | 3 | 20 | -- | YES | 12 weeks | N | -- | YES | 100% | 0% | 0% |
| Financial Mathematics | MTH3025 | 3 | 20 | -- | YES | 12 weeks | N | -- | YES | 20% | 10% | 70% |
| Geometry of Optimisation | MTH4323 | 3 | 20 | YES | -- | 12 weeks | Y | -- | YES | 20% | 0% | 80% |
| Investigations | AMA3020 | 3 | 20 | -- | YES | 12 weeks | N | YES | -- | 80% | 20% | 0% |
| Quantum Fields | MTH4331 | 3 | 20 | -- | YES | 12 weeks | N | -- | YES | 20% | 20% | 60% |
| Concurrent Programming | CSC3021 | 3 | 20 | YES | -- | 12 weeks | Y | -- | YES | 100% | 0% | 0% |
| Quantum Theory | MTH3032 | 3 | 20 | YES | -- | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Project | PMA4001 | 4 | 40 | YES | YES | 24 weeks | N | YES | -- | 80% | 20% | 0% |
| Advanced Quantum Theory | MTH4031 | 4 | 20 | YES | -- | 12 weeks | N | -- | YES | 0% | 20% | 80% |
| Algorithms: Analysis and Application | CSC4003 | 4 | 20 | -- | YES | 12 weeks | Y | YES | -- | 20% | 0% | 80% |
| Quantum Fields | MTH4331 | 4 | 20 | -- | YES | 12 weeks | N | -- | YES | 20% | 20% | 60% |
| Geometry of Optimisation | MTH4323 | 4 | 20 | YES | -- | 12 weeks | N | -- | YES | 20% | 0% | 80% |
| Topology | MTH4011 | 4 | 20 | YES | -- | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Mathematical Methods for Quantum Information Processing | MTH4023 | 4 | 20 | -- | YES | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Project | AMA4005 | 4 | 40 | YES | YES | 24 weeks | N | YES | -- | 80% | 20% | 0% |
| Information Theory | MTH4022 | 4 | 20 | -- | YES | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Integration Theory | PMA4004 | 4 | 20 | YES | -- | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Applied Algebra and Cryptography | MTH4021 | 4 | 20 | -- | YES | 12 weeks | N | -- | YES | 20% | 0% | 80% |
| Fourier Analysis and Applications to PDEs | MTH4321 | 4 | 20 | -- | YES | 12 weeks | N | -- | YES | 30% | 0% | 70% |
| Digital Transformation: Software Design, Management and Practical Implementation | CSC4008 | 4 | 20 | YES | -- | 12 weeks | N | YES | -- | 100% | 0% | 0% |
| Practical Methods for Partial Differential Equations | MTH4024 | 4 | 20 | YES | -- | 12 weeks | N | -- | YES | 30% | 0% | 70% |
Notes
At Stage 4, Students must take a 40 CATS project module (PMA4001 or AMA4005), CSC4008 and CSC4003, and two modules of Mathematics, the combination of which is dependant on the Analysis, Algebra, Quantum or Modelling stream as indicated in further information provided by the school each year.
Further details on prerequisites can be found on Qsis course catalogue.
At Stage 1, Students are required to take the SIX compulsory modules listed.
At Stage 2, Students must take must take six Level 2 modules, with at least two modules from Mathematics, including MTH2011, and at least two modules from Computer Science, including CSC2059.
In choosing their optional modules, students should take note of pre-requisites for Level 3 Mathematics modules. Students intending to pursue the Analysis stream should take MTH2012 and MTH2013. Students intending to pursue the Algebra stream should take MTH2014. Students intending to pursue the Quantum stream should take MTH2031 and MTH2021. Students intending to pursue the Modelling stream should take MTH2021.
In addition, students planning to take a placement year must take MTH2010.
At Stage 3, students must take a combination as approved by their Advisor of Studies, of six Level 3 modules, the combination of which is dependant on the Analysis, Algebra, Quantum or Modelling stream as indicated in further information provided by the school each year.
Student must take either AMA3020 or PMA3013.
The choices must include at least two modules from Computer Science.