Mathematics and Computer Science

Leeds University Business School

Postgraduate

In Leeds

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Description

  • Type

    Postgraduate

  • Location

    Leeds

  • Start date

    Different dates available

This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. You’ll be introduced to sophisticated techniques at the forefront of both disciplines.
The programme combines teaching and research from the School of Mathematics and the School of Computing. Based on the Schools’ complementary research strengths the programme follows two main strands:
- Algorithms and complexity theory
- Numerical methods and parallel computing
You’ll have the choice to specialise in one of these strands, gaining specialist knowledge and skills that will prepare you for a wide range of careers. You’ll also develop your research skills when you complete your dissertation.
If you do not meet the full academic entry requirements then you may wish to consider the Graduate Diploma in Mathematics. This course is aimed at students who would like to study for a mathematics related MSc course but do not currently meet the entry requirements. Upon completion of the Graduate Diploma, students who meet the required performance level will be eligible for entry onto a number of related MSc courses, in the following academic year.

Facilities

Location

Start date

Leeds (North Yorkshire)
Maurice Keyworth Building, The University Of Leeds, LS2 9JT

Start date

Different dates availableEnrolment now open

About this course

Entry requirements
A BSc degree with a 2:1 (hons) in mathematics or computer science (with a substantial mathematics component), or equivalent. We will also consider students who hold other degrees with a substantial mathematics component.
We accept a range of international equivalent qualifications.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in all components. For other English qualifications, read English language equivalent qualifications.
Improve your English ks) and Language for Science: General Science (10 weeks).
How to apply
Application...

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This centre's achievements

2018

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 14 years

Subjects

  • GCSE Mathematics
  • Computational
  • School
  • Mathematics
  • Algorithms
  • Computing

Course programme

It is expected that you will specialise in one of two areas during the course, although this is not essential.

The two strands are:

Algorithms and complexity theory and connections to logic and combinatorics

This concerns the efficiency of algorithms for solving computational problems, and identifies hierarchies of computational difficulty. This subject has applications in many areas, such as distributed computing, algorithmic tools to manage transport infrastructure, health informatics, artificial intelligence, and computational biology.

Numerical methods and parallel computing

Many problems in mathematics, physics, astrophysics and biology cannot be solved using analytical techniques and require the application of numerical algorithms for progress. The development and optimisation of these algorithms coupled with the recent increase in computing power via the availability of massively parallel machines has led to great advances in many fields of computational mathematics. This subject has applications in many areas, such as combustion, lubrication, atmospheric dispersion, river and harbour flows, and many more.

Course structure

These are typical modules/components studied and may change from time to time. Read more in our Terms and conditions.

Modules Year 1

Optional modules

  • Machine Learning 10 credits
  • Combinatorial Optimisation 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • MSc Project 60 credits
  • Bio-Inspired Computing 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Knowledge Representation and Machine Learning 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits
  • Calculus in the Complex Plane 15 credits
  • Philosophy of Logic and Mathematics 20 credits
  • Graph Theory 15 credits
  • Number Theory 15 credits
  • Groups and Symmetry 15 credits
  • Proof and Computation 15 credits
  • Differential Geometry 15 credits
  • Models and Sets 15 credits
  • Combinatorics 15 credits
  • Coding Theory 15 credits
  • Commutative Rings and Algebraic Geometry
  • ...

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Mathematics and Computer Science

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