GG41 - Queen Mary University of London

Programme Title: BSc Computer Science & Mathematics 

Programme Specification 

Awarding Body/Institution 

Teaching Institution 

Queen Mary, University of London 

Queen Mary, University of London 

Name of Final Award and Programme Title BSc (Hons) Computer Science & Mathematics 

Duration of Study / Period of Registration 

QM Programme Code / UCAS Code(s) 

QAA Benchmark Group 

3 years 

GG41 

Computer Science, Mathematics 

FHEQ Level of Award Level 6 

Programme Accredited by 

N/A 

Date Programme Specification Approved 31 Mar 2011 

Responsible School / Institute 

School of Electronic Engineering & Computer Science 

Schools also involved in teaching part of the programme 

Programme Rationale 

This programme aims to equip students with a sound, reflective understanding of both computer science and mathematics and 

of how they are related, together with the skills necessary to apply these skills in conjunction to analyse and solve real-world 

problems and to develop, on the basis of these solutions, effective computer systems. 

Educational Aims of the Programme 

Practically, the program equips the students with the ability to use a modern programming language - currently Java - and a 

modern symbolic computation system - currently Maple. Students will also acquire skills in the construction of computer 

programs, in calculation (both by hand and aided by computers) and will have a grounding in the analysis and application of 

algorithms, both numerical and non-numerical. They will also have enough perspective to be able to choose between different 

programming and analytical paradigms to find an appropriate one for the solution of a given problem. 

This program incorporates, on the computing side, a solid grounding in programming, computer systems, and in the formal 

tools of computer science; on the mathematical side, it has a basis of both discrete and continuous mathematics. There are many 

possible combinations of this palette of disciplines, and the programme is flexible enough to allow a certain degree of choice: 

for example, students could specialise in the logic and formal analysis of computer programmes, or in machine learning, or 

could apply computational techniques to mathematical problems in combinatorics or in dynamical systems. Equally, they could 

use dynamical systems theory to analyse the computational techniques that are used in modern banking. All of these


combinations will give the students a good understanding of the theory and application of both mathematics and computer 

science in the modern world. 

Students will, throughout their development, learn practical skills, both computational and mathematical, in a laboratory 

environment: students will gain experience of solving problems, and applying their skills, in a series of progressively more 

demanding applications. 

Alongside this, the programme pays attention to the wider context of both mathematics and computing and the development 

of transferable skills such as writing, presentation and team work. The programme is under continual revision to ensure it 

matches the needs of both students and their future employers. 

Learning Outcomes 

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, 

skills and other attributes in the following areas. The programme outcomes are referenced to the relevant QAA 

benchmark statement(s) (see above) and the Framework for Higher Education Qualifications in England, Wales 

and Northern Ireland (2008), and relate to the typical student. Additionally, the SEEC Credit Level Descriptors 

for Further and Higher Education 2003 and Queen Mary Statement of Graduate Attributes have been used as a 

guiding framework for curriculum design. 

Knowledge and understanding of: 

A 1 

A 2 

A 3 

A 4 

A 5 

A 6 

A 7 

computer system components and architecture 

the principles of operating systems and networks and the techniques required for their implementation 

specific operating systems 

the common protocols used in networks 

major application areas in the sciences, medicine, industry and commerce 

the mathematical, scientific and engineering elements of computer science 

the historical, social and professional context of computer science 

Intellectual skills - able to: 

B 1 

B 2 

B 3 

recognise and plan for the presence of risk in engineering practice 

solve complex practical problems in a logical and methodical way 

understand common protocols used in networks 

Transferable skills - able to: 

C 1 

manage projects effectively


C 2 

C 3 

produce well-written, accurate and complete technical documentation 

relate theoretical understanding to practical implementation in a diverse range of situations 

Practical skills - able to: 

D 1 

D 2 

D 3 

implement parts of an operating system 

work effectively as a member of a design and development team 

apply usability principles 

Teaching, Learning and Assessment Strategies 

All taught courses involve lectures, problem-solving courseworks and (where appropriate) practical sessions. Lectures are used to 

introduce principles, methods and techniques and, through the use of examples, to illustrate how they can be applied in 

practice. Courseworks allow students to develop their own skills in analysis, calculation, design and problem-solving and to gain 

extensive practical experience of building computer systems, or solving mathematical problems, using a wide range of tools and 

techniques. Practical sessions provide students with the guidance and help required to achieve this. These sessions take the form 

of programming laboratories, design studios, exercise classes and project consultancy meetings run by academic staff with the 

assistance of postgraduate students. On all our courses, students mostly 'learn through doing' and can expect to spend far longer 

in the teaching laboratory or in exercise classes than in lectures. Some core units include short essay writing courseworks to 

develop the skills that are vital for effective presentation of project work. 

Each year of study contains small group teaching sessions to encourage the development of reflective, insightful design, 

analytical, and written and verbal communication skills. In year 1 computer science tutorials help students adapt to independent 

study and develop their study and communication skills through a series of research and presentation exercises. The Software 

Engineering team project in year 2 (if taken) and the final year individual Computer Science Project include consultancy meetings 

where students report on their progress, discuss their designs and plan their future work: GG41 students will be encouraged to 

choose a project topic which is relevant for their mathematical studies as well as for computer science. All of these activities 

reinforce and develop the ability to communicate technical ideas clearly and effectively and, in addition, to synthesise, and reflect 

on, ideas and techniques from different parts of the syllabus. 

Many of the taught modules, especially in Computer Science, are assessed through a written examination and practical 

courseworks. Where appropriate, courseworks are examined using live demonstrations in which students give a technical 

presentation of their work. Some modules also include in-term tests as a component in assessment. Projects are examined on the 

basis of a written report and formal oral presentation. 

Programme Structure(s) and Requirements, Levels and Modules 

Students must complete 120 credits in each developmental year. All modules are 15 credits with the exception of the Computer 

Science Project (30 credits) 

YEAR 1, SEMESTER 1 

DCS100 Procedural Programming 

DCS113 Logic and Discrete Structures 

MTH4107 Introduction to Probability 

MTH4100 Calculus I 

YEAR 1, SEMESTER 2


DCS104 Object Oriented Programming 

DCS103 Language and Communication 

MTH4104 Introduction to Algebra 

MTH4101 Calculus II 


DCS210 Algorithms & Data Structures in an OO Framework 

MTH4103 Geometry I 

plus 2 of the following: 

DCS234 Software Engineering Theory 

DCS200 Essential Networks & Operating Systems 

MTH5104 Convergence and Continuity 

MTH5102 Calculus III 

MTH5121 Probability Models 


DCS225 Database Systems 

MTH4106 Introduction to Statistics 

plus 2 of the following, including (in this semester or in Semester 6) MTH5110: 

DCS201 Further Networks and Operating Systems 

DCS224 Graphical User Interfaces 

MTH5100 Algebraic Structures I 

MTH5103 Complex Variables 

MTH5105 Differential & Integral Analysis 

MTH5109 Geometry II: Knots and Surfaces 

MTH6105 Algorithmic Graph Theory 

MTH6128 Number Theory 


DCS334 Computer Science Project (30 credits) 

DCS333 Algorithms & Complexity 

Plus 2 from the following: 

DCS314 Computer Graphics 

MTH5102 Calculus III 

MTH5112 Linear Algebra I 

MTH6109 Combinatorics 

MTH6104 Algebraic Structures II 

MTH6107 Chaos and Fractals 


DCS334 Computer Science Project (30 credits) contd 

Plus 3 from the following: 

DCS301 Computability 

DCS303 Computational Genomics 

DCS306 High Performance Computing 

ELE611 Artificial Intelligence 

ELE041 Machine Learning 

DCS337 Software Risk Assessment 

MTH5100 Algebraic Structures I 

MTH5103 Complex Variables 

MTH6105 Algorithmic Graph Theory 

MTH6108 Coding Theory 

MTH6128 Number Theory 

MTH6115 Cryptography 

MTH6162 Metric Spaces 

A minimum of two 2 course units in the final year must be taken in Mathematics.


Module Title 

Module 

Code 

Credits 

Level 

Module 

Selection 

Status 

Academic 

Year of 

Study 

Semester 

X Procedural Programming DCS100 15 4 Compulsory 1 Semester 1 

X Logic & Discrete Structures DCS113 15 4 Compulsory 1 Semester 1 

X Introduction to Probabilty MTH4107 15 4 Compulsory 1 Semester 1 

X Calculus I MTH4100 15 4 Compulsory 1 Semester 1 

X Object Oriented Programming DCS104 15 4 Compulsory 1 Semester 2 

X Language & Communication DCS103 15 4 Compulsory 1 Semester 2 

X Introduction to Algebra MTH4104 15 4 Compulsory 1 Semester 2 

X Calculus II MTH4101 15 4 Compulsory 1 Semester 2 

X 

Algorithms & Data Structures in an 

OO Framework 

DCS210 15 5 Compulsory 2 Semester 1 

X Geometry I MTH4103 15 5 Compulsory 2 Semester 1 

X Software Engineering Theory DCS234 15 5 Elective 2 Semester 1 

X 

Essential Networks & Operating 

Systems 

DCS200 15 5 Elective 2 Semester 1 

X Convergence & Continuity MTH5104 15 5 Elective 2 Semester 1 

X Calculus III MTH5102 15 5 Elective 2 Semester 1 

X Probability Models MTH5121 15 5 Elective 2 Semester 1 

X Database Systems DCS225 15 5 Compulsory 2 Semester 2 

X Introduction to Statistics MTH4106 15 5 Compulsory 2 Semester 2 

X 

Further Networks and Operating 

Systems 


X Graphical User Interfaces DCS224 15 5 Elective 2 Semester 2


X Algebraic Structures I MTH5100 15 5 Elective 2 Semester 2 

X Complex Variables MTH5103 15 5 Elective 2 Semester 2 

X Differential & Integral Analysis MTH5105 15 5 Elective 2 Semester 2 

X Geometry II: Knots and Surfaces MTH5109 15 5 Elective 2 Semester 2 

X Algorithmic Graph Theory MTH6105 15 5 Elective 2 Semester 2 

X Number Theory MTH6128 15 5 Elective 2 Semester 2 

X Computer Science Project DCS334 30 6 Compulsory 3 Semesters 1 & 2 

X 

Computer Graphics 


X Algorithms & Complexity DCS333 15 6 Compulsory 3 Semester 1 

X Calculus III MTH5102 15 6 Elective 3 Semester 1 

X Linear Algebra I MTH5112 15 6 Elective 3 Semester 1 

X Combinatorics MTH6109 15 6 Elective 3 Semester 1 

X Algebraic Structures II MTH6104 15 6 Elective 3 Semester 1 

X Chaos & Fractals MTH6107 15 6 Elective 3 Semester 1 

X Computability DCS301 15 6 Elective 3 Semester 2 

X Computational Genomics DCS303 15 6 Elective 3 Semester 2 

X High Performance Computing DCS306 15 6 Elective 3 Semester 2 

X Artificial Intelligence ELE611 15 6 Elective 3 Semester 2 

X Machine Learning ELE041 15 6 Elective 3 Semester 2 

X Software Risk Assessment DCS337 15 6 Elective 3 Semester 2 

X Algebraic Structures I MTH5100 15 6 Elective 3 Semester 2


X Complex Variables MTH5103 15 6 Elective 3 Semester 2 

X Algorithmic Graph Theory MTH6105 15 6 Elective 3 Semester 2 

X Coding Theory MTH6108 15 6 Elective 3 Semester 2 

X Number Theory MTH6128 15 6 Elective 3 Semester 2 

X Cryptography MTH6115 15 6 Elective 3 Semester 2 

X Metric Spaces MTH6162 15 6 Elective 3 Semester 2 

Criteria for Admission to the Programme 

2011 entry: 280 UCAS tariff points including A Level Mathematics (B or above) 

2012 entry: 340 UCAS tariff points including either an A grade in A-level Maths or B grades in both A-level Maths and Further 

Maths. 

Quality Assurance Mechanism 

Include details of: SSLC meetings, student feedback mechanisms, personal tutor arrangements, programme 

induction, programme review and monitoring. 

There are two SSLC meetings in the first and second semesters. Students also complete a module feedback questionnaire. Each 

student is allocated academic advisor. 

There is a general introduction to the programme on the first day of the session followed by a more specialised induction in the 

Informatics Teaching Laboratory. 

There is a College Annual Review of Taught programmes. The School also reviews its curriculum, normally once every four years. 

Programme-specific Assessment Regulations (if applicable) 

In the case of programmes that deviate / do not comply with the Academic Regulations further information 

regarding the nature of any difference and/or deviation should be stipulated in detail. 

N/A


Employers Links 

Please provide details of any links with employers e.g. 

· Details of advisory panels that include current or potential employers; 

· Organisations that regularly employ graduates from this programme and the roles that graduates 

undertake. 

· Student prizes donated by organisations that may offer employment to graduates from this programme. 

If there are no links with employers consider the learning outcomes and transferable skills and explain how 

these might be used to inform employers about the qualities and skills a graduate from this programme might 

be expected to have. 

The School of Electronic Engineering & Computer Science has a wide range of industrial contacts secured through research 

projects and consultancy, our Industrial Experience programme, our Industrial Advisory Board and our Doctoral Training Centre. 

The Industrial Advisory Board works to ensure that our courses are state of the art and match the changing requirements of this 

fast moving industry. The Board includes representatives from a variety of Computer Science orientated companies ranging from 

SMEs to major blue-chips. These include: Microsoft Research, Royal Bank of Scotland, BT Labs, Oaklodge Consultancy, Intel 

Research, The Usability Company, Hewlett Packard Labs and Arclight Media Technology Limited 

Recent graduates have found employment as programmers, Systems Analysts, Software Engineers, database developers, IT 

consultants and web developers with well known multinational companies throughout the UK and Europe, the Americas and 

Asia - Merril Lynch, Microsoft, Nokia, Barclays Capital, Logica, JPMorgan and Bear Sterns are among the organizations that have 

recently employed graduates of EECS programs. 

Career Opportunities: 

Graduates can enter many different disciplines and vocations such as banking, mobile phone companies, the NHS, newspapers, 

schools, IT consultancies and financial consultancies. A significant proportion of graduates obtain jobs in the software industry - 

as systems analysts, programmers, database managers or working in e-commerce - in a variety of companies. Others find 

employment in jobs that make use of their communication and analysis skills such as management consultancy. 

Programme Specification Approval 

Person completing Programme Specification 

Graham White/Malcolm Smith 

Person responsible for management of programme Graham White 

Date Programme Specification produced/amended 

by School or teaching and learning committee 

Date Programme Specification approved by 

Programme and Module approval Board 

March 2011 

31 Mar 2011

GG41 - Queen Mary University of London

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