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MSci Mathematics and 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

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

JACS Code

G100 (DESCR) 50

Criteria for Admissions

Stage 1 Entry: 3 A-levels AAA (or equivalent) grade A Mathematics

ATAS Clearance Required

No

Health Check Required

No

Portfolio Required

Interview Required

Mode of Study

Full Time

Type of Programme

Undergraduate Master

Length of Programme

4 Academic Year(s)

Total Credits for Programme

480

Exit Awards available

INSTITUTE INFORMATION

Awarding Institution/Body

Queen's University Belfast

Teaching Institution

Queen's University Belfast

School/Department

Mathematics & Physics

Framework for Higher Education Qualification Level 
http://www.qaa.ac.uk/publications/information-and-guidance

Level 7

QAA Benchmark Group
http://www.qaa.ac.uk/assuring-standards-and-quality/the-quality-code/subject-benchmark-statements

Mathematics, Statistics and Operational Research (2015)

Accreditations (PSRB)

Institute of Mathematics and its Applications

Date of most recent Accreditation Visit 04-06-13

External Examiner Name:

External Examiner Institution/Organisation

Professor J Kedra (Pure Maths)

University of Aberdeen

Professor Y Fyodorov (Applied Maths)

Queen Mary, University of London

Professor M G Moller (Computer Science)

Swansea University

REGULATION INFORMATION

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

No

Programme Specific Regulations

Students will not be permitted to register for Stage 2 unless they have passed all their core Level 1 modules.

Transfers to Other Pathways
At the end of Stage 2, Students may transfer to other Pathways (BSc, or if they have achieved a weighted average of at least 55%, before rounding MSci), provided they have passed all the compulsory modules on the Pathway to which they are transferring up to that time of transfer.

Progression
At the end of Stages 2 and 3, students require an overall weighted average of at least 55% before rounding to progress to the next stage.
At the end of stages 2 and 3, students with an overall weighted average of less than 55% before rounding will be required to transfer to the BSc degree.

To progress from stage 3 to stage 4 students must maintain a weighted average of at least 55% before rounding
Students who fail to maintain this average will be required to transfer to the BSc pathway. They may be awarded a BSc degree if they meet the criteria for this award.

Students with protected characteristics

N/A

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 Skills

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

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.

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

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.

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.

Learning Outcomes: Knowledge & Understanding

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

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

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

Application of the fundamental concepts is also of importance to any of the project modules, as deeper understanding will result in higher marks

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

This appreciation is of particular importance to the project modules, as mathematical logic is critical to arrive at appropriate mathematical conclusions

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

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.

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

Learning Outcomes: Subject Specific

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

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.

The project modules allow students to spend time on a more extended problem, which will enable a more in-depth development of mathematical arguments and application mathematical techniques

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.

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.

The project modules allow students to spend time on a more extended problem, which will enable a more in-depth development of mathematical arguments and application mathematical techniques

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.

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.

In the project modules, further opportunities to use mathematical software may be available.

Methods of Assessment

These skills are primarily assessed through reports and presentations associated with work carried out using mathematical software.

Present mathematical findings accurately through oral and written means to a range of audiences
Prepare accurate technical reports and give accurate technical presentations on computer systems

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.

Learning Outcomes: Transferable Skills

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

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.

It is also a critical skill developed during the project modules

Methods of Assessment

Analytic thinking is embedded implicitly in every assessment within mathematics.

Problem solving skills will be assessed through an extended range of project work, culminating in the final-year project modules

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

Basic mathematical modelling skills are developed through the mathematical modelling module and the computer algebra module. Numerical analysis and statistics oriented modules have associated computer –oriented tasks, where students can develop skills in the use of appropriate specialist software

In the project modules, further opportunities to use mathematical software may be available.

Written reports develop skills in the use of word-processing software, while the presentations can develop skills in the use of presentation software

Methods of Assessment

Assessed through practical work, projects, assignments and other coursework activities and individual learning

Computer modelling skills are primarily assessed through reports and presentations associated with work carried out using mathematical software.

The main test in Computer Algebra takes place through a direct assessment of their use of appropriate software

Computer skills in word-processing and presentation development are assessed implicitly in the project and presentation assessment

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.
Any report or presentation will provide an explicit learning opportunity, where the increase in mathematical difficulty at higher levels will provide a means for communication skill development

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

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.
Any report or presentation will provide an explicit learning opportunity, where the increase in mathematical difficulty at higher levels will provide a means for communication skill development

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

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

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.

Learning Outcomes: Cognitive Skills

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

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 & Understanding

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

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 Specific

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

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

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

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 Skills

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

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

Programme Requirements

Module Title

Module Code

Level/ stage

Credits

Availability

Duration

Pre-requisite

 

Assessment

 

 

 

 

S1

S2

 

 

Core

Option

Coursework %

Practical %

Examination %

Fluid Mechanics

AMA2005

2

20

YES

12 weeks

Y

YES

20%

0%

80%

Analysis

PMA2002

2

20

YES

12 weeks

Y

YES

40%

0%

60%

Electromagnetic Theory

AMA3001

3

20

YES

12 weeks

N

YES

30%

0%

70%

Quantum Theory

AMA3002

3

20

YES

12 weeks

N

YES

30%

0%

70%

Linear & Dynamic Programming

SOR3001

3

20

YES

12 weeks

Y

YES

10%

20%

70%

Tensor Field Theory

AMA3003

3

20

YES

12 weeks

N

YES

0%

20%

80%

Numerical Analysis

AMA2004

2

20

YES

12 weeks

Y

YES

10%

40%

50%

Partial Differential Equations

AMA3006

3

20

YES

12 weeks

N

YES

0%

20%

80%

Advanced Quantum Theory

AMA4001

4

20

YES

12 weeks

N

YES

20%

0%

80%

Advanced Mathematical Methods

AMA4003

4

20

YES

12 weeks

N

YES

10%

20%

70%

Classical Mechanics

AMA2001

2

20

YES

12 weeks

Y

YES

40%

0%

60%

Statistical Mechanics

AMA4004

4

20

YES

12 weeks

Y

YES

50%

0%

50%

Project

AMA4005

4

40

24 weeks

N

YES

100%

0%

0%

Investigations

AMA3020

3

20

YES

12 weeks

N

YES

100%

0%

0%

Practical Methods for Partial Differential Equations

AMA4006

4

20

YES

12 weeks

N

YES

0%

50%

50%

Group Theory

PMA2008

2

20

YES

12 weeks

Y

YES

20%

0%

80%

Professional Computing Practice

CSC2011

2

10

24 weeks

N

YES

85%

15%

0%

Computer Algebra

PMA3008

3

20

YES

12 weeks

N

YES

0%

100%

0%

Ring Theory

PMA3012

3

20

YES

12 weeks

Y

YES

20%

0%

80%

Set Theory

PMA3014

3

20

YES

12 weeks

Y

YES

0%

30%

70%

Topology

PMA4003

4

20

YES

12 weeks

Y

YES

0%

30%

70%

Integration Theory

PMA4004

4

20

YES

12 weeks

Y

YES

30%

0%

70%

Financial Mathematics

AMA3007

3

20

YES

12 weeks

N

YES

30%

0%

70%

Mathematical Investigations

PMA3013

3

20

YES

12 weeks

N

YES

100%

0%

0%

Functional Analysis

PMA4002

4

20

YES

12 weeks

Y

YES

40%

0%

60%

Project

PMA4001

4

40

24 weeks

N

YES

100%

0%

0%

Concurrent Programming

CSC3021

3

20

YES

12 weeks

Y

YES

50%

50%

0%

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

60%

0%

40%

Formal Methods

CSC3001

3

20

YES

12 weeks

Y

YES

30%

0%

70%

Calculus of Variations & Hamiltonian Mechanics

AMA3013

3

20

YES

12 weeks

N

YES

30%

0%

70%

Mathematical Modelling in Biology and Medicine

AMA3014

3

20

YES

12 weeks

N

YES

20%

30%

50%

Information Theory

AMA4009

4

20

YES

12 weeks

N

YES

30%

0%

70%

Metric and Normed Spaces

PMA3017

3

20

YES

12 weeks

Y

YES

20%

0%

80%

Algebraic Equations

PMA3018

3

20

YES

12 weeks

Y

YES

20%

0%

80%

Algebraic Topology

PMA4010

4

20

YES

12 weeks

Y

YES

30%

0%

70%

Mathematical Methods for Quantum Information Processing

AMA4021

4

20

YES

12 weeks

N

YES

30%

0%

70%

Data Structures, Algorithms and Programming Languages

CSC2040

2

30

24 weeks

Y

YES

30%

30%

40%

Software Development - Processes and Practice

CSC2044

2

30

24 weeks

Y

YES

100%

0%

0%

Theory of Computation

CSC2047

2

30

24 weeks

Y

YES

60%

0%

40%

Analysis and Calculus

AMA1020

1

30

24 weeks

N

YES

10%

0%

90%

Numbers, Vectors and Matrices

PMA1020

1

30

24 weeks

N

YES

10%

0%

90%

Mathematical Reasoning

PMA1021

1

10

YES

12 weeks

N

YES

100%

0%

0%

Mathematical Modelling

AMA1021

1

10

YES

12 weeks

N

YES

80%

20%

0%

Programming

CSC1020

1

40

24 weeks

N

YES

30%

70%

0%

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%

Introduction to Partial Differential Equations

AMA2008

2

10

YES

6 weeks

Y

YES

60%

40%

0%

Graph Theory

PMA2021

2

20

YES

12 weeks

Y

YES

20%

0%

80%

Linear Algebra & CV

PMA2020

2

30

18 weeks

Y

YES

10%

0%

90%

Notes

At Stage 1 Students are required to take the FIVE compulsory modules listed.

At Stage 2 Students must take an approved combination of modules for a total of 120 CATS points chosen from the list. The choice must include AMA2008, PMA2020 and at least 40 CATS credits of Computer Science modules, including CSC2040 Data Structures, Algorithms and Programming Languages. To avail of the full range of Pure Mathematics modules at Level 3 Students should include PMA2002 in their choice. Not every module will be offered every year.

At Stage 3 Students must take an approved combination of Level 3 modules for a total of 120 CAT Points chosen from the list. Students intending to take a Pure Mathematics project at Level 4 must include PMA3013, PMA3014 and PMA3017. Students intending to take an Applied Mathematics project at Level must include AMA3020, and either AMA3002 or AMA3006. The weight of Computer Science modules taken must be at least 40 CATS credits. Not every module will be offered every year.

Stage 4. Students must choose a project module in either Applied Mathematics (AMA4005) or Pure Mathematics (PMA4001), CSC4002 and CSC4003. If a project in Applied Mathematics is chosen, then the two remaining modules must be chosen from those offered in Applied Mathematics, while if a project in Pure Mathematics is chosen, the two remaining modules must be chosen from those offered in Pure Mathematics.