2021/22 Undergraduate Programme Catalogue
MSci, BSc Computer Science and Mathematics
Programme code: | MSBS-CS&MATH | UCAS code: | G4G2 |
---|---|---|---|
Duration: | 4 Years | Method of Attendance: | Full Time |
Programme manager: | Dr Isolde M Adler | Contact address: | I.M.Adler@leeds.ac.uk |
Total credits: 480
Entry requirements:
A-level: AAA including Mathematics, excluding General Studies.
IT or Engineering Diploma: Grade A (plus A or above in A-level Mathematics).
BTEC Extended Diploma: Grade D*DD including a D in Further Mathematics.
IB: 35 points overall, with 18 points at higher level to include 5 points in higher level Mathematics.
School/Unit responsible for the parenting of students and programme:
School of Computing
Examination board through which the programme will be considered:
School of Computing
Relevant QAA Subject Benchmark Groups:
Programme specification:
The programme will:
produce graduates with the broad-based core practical skills expected by industry. The four-year programme will equip students with deeper experience of foundations or technologies, informed by the two School’s research.
The programme provides a Computer Science and Mathematics core in the first year (level 1) to focus on core learning objectives. Specialisation is possible at level 2, with further specialisation at level 3 through the introduction of modules related to research topics that can be studied in more depth in the level 3 project and at level 5.
Guidance on these specialisations is provided by three streams, which naturally combine Mathematics and Computing and draw on the research expertise of both Schools. These streams are: (a) discrete mathematics; (b) scientific computation; and (c) complex systems.
(a) The discrete mathematics stream explores development, analysis and application of algorithms for computationally hard problems from optimization, graph theory, and logic. This provides the key foundations for developments in computer networking and security.
(b) Scientific computation focuses on analysis and implementation of high-performance and parallel numerical algorithms. Application areas include fluid dynamics, combustion and atmospheric dispersion.
(c) The complex systems specialism lays the foundation for the interdisciplinary study of the world around us, from genetics to ecology; from neuroscience to social networks; and from finance to the web. As a discipline it combines the study of dynamical systems with data driven analysis and statistical or computational modelling.
These streams will naturally extend into the Master level with a sufficient number of specialised level 3 and level 5 modules already in place, among them Algorithms, Graph Theory: Structure and Algorithms, Scientific Computation, Scientific Visualization, Scheduling, and Knowledge Representation and Machine Learning (all Computing) as well as numerous options from the Mathematics side (the programme catalogue for the MSc ‘Mathematics and Computer Science’ currently lists 86 modules, 71 of them offered by Mathematics, though not all of them running each year).
A research-based learning approach is used throughout the programme. Modules at all levels use examples of the latest technologies and methods from current research and provide opportunities for students to develop and demonstrate research skills.
Students undertake individual and team projects at all levels of the programme providing an opportunity to consolidate their knowledge and skills.
MSc students are given additional research experience and professional and management experience through research specialisms and a Group Project at level 4.
Year1 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Compulsory modules:
Candidates will be required to study the following compulsory modules:
COMP1121 | Databases | 10 credits | Semester 2 (Jan to Jun) | |
COMP1212 | Computer Processors | 10 credits | Semester 2 (Jan to Jun) | |
COMP1511 | Introduction to Discrete Mathematics | 10 credits | Semester 2 (Jan to Jun) | |
COMP1711 | Procedural Programming | 10 credits | Semester 1 (Sep to Jan) | |
COMP1721 | Object Oriented Programming | 10 credits | Semester 2 (Jan to Jun) | |
MATH1005 | Core Mathematics | 50 credits | Semesters 1 & 2 (Sep to Jun) | |
MATH1025 | Number Systems | 15 credits | Semester 1 (Sep to Jan) | |
MATH1710 | Probability and Statistics I | 10 credits | Semester 1 (Sep to Jan) |
Optional modules:
Year2 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Compulsory modules:
Candidates will be required to study the following compulsory modules:
COMP2121 | Data Mining | 10 credits | Semester 2 (Jan to Jun) | |
COMP2321 | Formal Languages and Finite Automata | 10 credits | Semester 2 (Jan to Jun) | |
COMP2421 | Numerical Computation | 10 credits | Semester 1 (Sep to Jan) | |
COMP2611 | Artificial Intelligence | 10 credits | Semester 2 (Jan to Jun) | |
COMP2711 | Algorithms and Data Structures I | 10 credits | Semester 1 (Sep to Jan) | |
COMP2721 | Algorithms and Data Structures II | 10 credits | Semester 2 (Jan to Jun) | |
COMP2932 | Compiler Design and Construction | 10 credits | Semester 2 (Jan to Jun) | |
MATH2022 | Groups and Vector Spaces | 15 credits | Semester 1 (Sep to Jan) | |
MATH2041 | Logic | 10 credits | Semester 1 (Sep to Jan) | |
MATH2365 | Vector Calculus | 15 credits | Semester 1 (Sep to Jan) | |
MATH2375 | Linear Differential Equations and Transforms | 15 credits | Semester 2 (Jan to Jun) |
Optional modules:
Year3 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Compulsory modules:
Candidates will be required to study the following compulsory modules:
COMP3931 | Individual Project | 40 credits | Semesters 1 & 2 (Sep to Jun) | |
COMP3940 | Graph Algorithms and Complexity Theory | 10 credits | Semester 1 (Sep to Jan) |
Optional modules:
Candidates must take 70 or 75 credits of options from the following list. These must consist of at least 40 MATH credits and at least 20 COMP credits. The remaining 20 credits will be selected from the MATH and COMP modules listed.
Candidates must take 70 or 75 credits of options from the following list. These must consist of at least 40 MATH credits and at least 20 COMP credits. The remaining 20 credits will be selected from the MATH and COMP modules listed.
COMP3211 | Distributed Systems | 10 credits | Semester 1 (Sep to Jan) | |
COMP3221 | Parallel Computation | 10 credits | Semester 2 (Jan to Jun) | |
COMP3223 | Cryptography | 10 credits | Semester 2 (Jan to Jun) | |
COMP3611 | Machine Learning | 10 credits | Semester 1 (Sep to Jan) | |
COMP3811 | Computer Graphics | 10 credits | Semester 1 (Sep to Jan) | |
COMP3910 | Combinatorial Optimisation | 10 credits | Semester 2 (Jan to Jun) | |
MATH3033 | Graph Theory | 15 credits | Semester 1 (Sep to Jan) | |
MATH3104 | Proof and Computation | 15 credits | Semester 2 (Jan to Jun) | |
MATH3143 | Combinatorics | 15 credits | Semester 2 (Jan to Jun) | |
MATH3365 | Mathematical Methods | 15 credits | Semester 1 (Sep to Jan) | |
MATH3374 | Linear and Non-Linear Waves | 15 credits | Not running in 202122 | |
MATH3565 | Mathematical Biology | 15 credits | Semester 1 (Sep to Jan) |
Year4 - View timetable
[Learning Outcomes, Transferable (Key) Skills, Assessment]
Compulsory modules:
Candidates will be required to study the following compulsory modules:
COMP5450M | Knowledge Representation and Reasoning | 15 credits | 1 Sep to 31 Jan (adv yr), Semester 1 (Sep to Jan) | |
COMP5930M | Scientific Computation | 15 credits | 1 Sep to 31 Jan (adv yr), Semester 1 (Sep to Jan) |
Optional modules:
Candidates will be required to study up to 90 or 95 credits of optional modules from the following lists. These must consist of up to a maximum of 45 COMP credits and up to a maximum of 55 MATH credits. You must complete and pass a total of 100 credits at Level 5M in order to be awarded the MSci degree.
COMP5530M | Group Project | 30 credits | Semester 2 (Jan to Jun), Semesters 1 & 2 (Sep to Jun) | |
COMP5611M | Machine Learning | 15 credits | Semester 1 (Sep to Jan), 1 Sep to 31 Jan (adv yr), Semester 2 (Jan to Jun) | |
COMP5623M | Artificial Intelligence | 15 credits | Semester 2 (Jan to Jun) | |
COMP5840M | Data Mining and Text Analytics | 15 credits | Semester 2 (Jan to Jun) | |
COMP5850M | Cloud Computing | 15 credits | Semester 2 (Jan to Jun) | |
COMP5911M | Advanced Software Engineering | 15 credits | 1 Sep to 31 Jan (adv yr), Semester 1 (Sep to Jan) | |
COMP5940M | Graph Theory: Structure and Algorithms | 15 credits | Semester 2 (Jan to Jun) |
MATH3033 | Graph Theory | 15 credits | Semester 1 (Sep to Jan) | |
MATH3044 | Number Theory | 15 credits | Not running in 202122 | |
MATH3104 | Proof and Computation | 15 credits | Semester 2 (Jan to Jun) | |
MATH3143 | Combinatorics | 15 credits | Semester 2 (Jan to Jun) | |
MATH3365 | Mathematical Methods | 15 credits | Semester 1 (Sep to Jan) | |
MATH3374 | Linear and Non-Linear Waves | 15 credits | Not running in 202122 | |
MATH3424 | Introduction to Entropy in the Physical World | 15 credits | Not running in 202122 | |
MATH3565 | Mathematical Biology | 15 credits | Semester 1 (Sep to Jan) | |
MATH5104M | Advanced Proof and Computation | 20 credits | Semester 2 (Jan to Jun) | |
MATH5366M | Advanced Mathematical Methods | 20 credits | Semester 1 (Sep to Jan) | |
MATH5373M | Advanced Linear and Nonlinear Waves | 20 credits | Not running in 202122 | |
MATH5424M | Advanced Entropy in the Physical World | 20 credits | Not running in 202122 | |
MATH5566M | Advanced Mathematical Biology | 20 credits | Semester 1 (Sep to Jan) |
Last updated: 23/02/2022 15:57:50
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