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Masters Degrees (Algorithmic)

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On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling. Read more
On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling.

We enable you to attain an understanding of financial markets at the level of individual trades occurring over sub-millisecond timescales, and apply this to the development of real-time approaches to trading and risk-management.

The course includes hands-on projects on topics such as order book analysis, VWAP & TWAP, pairs trading, statistical arbitrage, and market impact functions. You have the opportunity to study the use of financial market simulators for stress testing trading strategies, and designing electronic trading platforms.

In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas:
-Statistical and computational methods
-Modelling trading strategies and predictive services that are deployed by hedge funds
-Algorithmic trading groups
-Derivatives desks
-Risk management departments

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation. We are supported by Essex’s highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.

We are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of our research rated ‘world-leading’ or ‘internationally excellent (REF 2014).

Professional accreditation

This degree is accredited by the Institution of Engineering and Technology (IET).This accreditation is increasingly sought by employers, and provides the first stage towards eventual professional registration as a Chartered Engineer (CEng).

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching the development of real-time trading platforms, new financial econometric models for real-time data, the use of artificially intelligent agents in the study of risk and market-based institutions, operational aspects of financial markets, financial engineering, portfolio and risk management.

More broadly, our research covers a range of topics, from materials science and semiconductor device physics, to the theory of computation and the philosophy of computer science, with most of our research groups based around laboratories offering world-class facilities.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.
-We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress
-All computers run either Windows 7 or are dual boot with Linux
-Software includes Java, Prolog, C++, Perl, Mysql, Matlab, DB2, Microsoft Office, Visual Studio, and Project
-Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET)
-We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:
-HSBC
-Mitsubishi UFJ Securities
-Old Mutual
-Bank of England

We also work with the university’s Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-CCFEA MSc Dissertation
-Big-Data for Computational Finance
-High Frequency Finance and Empirical Market Microstructure
-Introduction to Financial Market Analysis
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Trading Global Financial Markets
-Cloud Technologies and Systems (optional)
-Constraint Satisfaction for Decision Making (optional)
-Creating and Growing a New Business Venture (optional)
-Digital Signal Processing (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Financial Engineering and Risk Management (optional)
-High Performance Computing (optional)
-Industry Expert Lectures in Finance (optional)
-Learning and Computational Intelligence in Economics and Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Text Analytics (optional)

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On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling. Read more
On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling.

We enable you to attain an understanding of financial markets at the level of individual trades occurring over sub-millisecond timescales, and apply this to the development of real-time approaches to trading and risk-management.

The course includes hands-on projects on topics such as order book analysis, VWAP & TWAP, pairs trading, statistical arbitrage, and market impact functions. You have the opportunity to study the use of financial market simulators for stress testing trading strategies, and designing electronic trading platforms.

In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas:

- Statistical and computational methods
- Modelling trading strategies and predictive services that are deployed by hedge funds
- Algorithmic trading groups
- Derivatives desks
- Risk management departments

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation. We are supported by Essex’s highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.

We are ranked Top 10 in the UK in the 2015 Academic Ranking of World Universities, with more than two-thirds of our research rated ‘world-leading’ or ‘internationally excellent (REF 2014).

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This interdisciplinary Masters degree provides you with a broad background in some mainstream and modern aspects of mathematics and computer science. Read more

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.

Course content

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 to 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.

For information on typical modules, read Mathematics and Computer Science MSc in the course catalogue

Learning and teaching

Teaching is carried out through a mixture of lectures and smaller group activities such as workshops. Most modules are assessed by a mix of coursework and written examinations. There is also the opportunity to complete a summer project which is individually supervised by a member of staff.

Assessment

The taught course is primarily assessed by end-of-semester examinations with a small component of continuous assessment. The semester three project is assessed by a written dissertation and a short oral presentation.

Career opportunities

Each of these areas offers many career options, and the MSc will provide you with both technical and transferrable skills, for example, conducting an extended and independent research project. It will also offer you excellent preparation for doctoral research in these or related subjects. On completion of the degree you can progress onto a wide range of opportunities including:

  • PhD in Mathematics, or in Computer Science
  • Careers in Computing and Industries which require algorithmic tools (transport infrastructure, health informatics, computational biology, artificial intelligence, companies developing the internet (e.g. search engines).
  • Many other careers (e.g. in Finance) where a mathematics background is valued.

In collaboration with both industrial and academic partners, our research has resulted in computational techniques, and software, that has been widely applied. Our industry links are extensive and include companies such as Google, Yahoo, Akamai, Microsoft, and Tracsis, as well as the NHS.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.



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This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. Read more
This highly focused MSc explores some of the mathematics behind modern secure information and communications systems, specialising in mathematics relevant for public key cryptography, coding theory and information theory. During the course critical awareness of problems in information transmission, data compression and cryptography is raised, and the mathematical techniques which are commonly used to solve these problems are explored.

The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography and our academic staff include several leading researchers in these areas. Students on the programme have the opportunity to carry out their dissertation projects in cutting-edge research areas and to be supervised by experts.

The transferable skills gained during the MSc will open up a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsofcryptographyandcommunications(msc).aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and a knowledge and understanding of the subjects of cryptography and communications preparing you for research or professional employment in this area.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course former students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses as well as complete a main project under the supervision of a member of staff.

Core courses:
Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed as well as methods for obtaining confidentiality and authentication.

Channels
In this unit, you will investigate the problems of data compression and information transmission in both noiseless and noisy environments.

Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Public Key Cryptography
This course introduces some of the mathematical ideas essential for an understanding of public key cryptography, such as discrete logarithms, lattices and elliptic curves. Several important public key cryptosystems are studied, such as RSA, Rabin, ElGamal Encryption, Schnorr signatures; and modern notions of security and attack models for public key cryptosystems are discussed.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- a suitable mathematical foundation for undertaking research or professional employment in cryptography and/or communications

- the appropriate background in information theory and coding theory enabling them to understand and be able to apply the theory of communication through noisy channels

- the appropriate background in algebra and number theory to develop an understanding of modern public key cryptosystems

- a critical awareness of problems in information transmission and data compression, and the mathematical techniques which are commonly used to solve these problems

- a critical awareness of problems in cryptography and the mathematical techniques which are commonly used to provide solutions to these problems

- a range of transferable skills including familiarity with a computer algebra package, experience with independent research and managing the writing of a dissertation.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications. Read more
This course covers a wide range of topics from both applied and applicable mathematics and is aimed at students who want to study the field in greater depth, in areas which are relevant to real life applications.

You will explore the mathematical techniques that are commonly used to solve problems in the real world, in particular in communication theory and in physics. As part of the course you will carry out an independent research investigation under the supervision of a member of staff. Popular dissertation topics chosen by students include projects in the areas of communication theory, mathematical physics, and financial mathematics.

The transferable skills gained on this course will open you up to a range of career options as well as provide a solid foundation for advanced research at PhD level.

See the website https://www.royalholloway.ac.uk/mathematics/coursefinder/mscmathematicsforapplications.aspx

Why choose this course?

- You will be provided with a solid mathematical foundation and knowledge and understanding of the subjects of cryptography and communications, preparing you for research or professional employment in this area.

- The Mathematics Department at Royal Holloway is well known for its expertise in information security and cryptography. The academics who teach on this course include several leading researchers in these areas.

- The mathematical foundations needed for applications in communication theory and cryptography are covered including Algebra, Combinatorics Complexity Theory/Algorithms and Number Theory.

- You will have the opportunity to carry out your dissertation project in a cutting-edge research area; our dissertation supervisors are experts in their fields who publish regularly in internationally competitive journals and there are several joint projects with industrial partners and Royal Holloway staff.

- After completing the course students have a good foundation for the next step of their career both inside and outside academia.

Department research and industry highlights

The members of the Mathematics Department cover a range of research areas. There are particularly strong groups in information security, number theory, quantum theory, group theory and combinatorics. The Information Security Group has particularly strong links to industry.

Course content and structure

You will study eight courses and complete a main project under the supervision of a member of staff.

Core courses:
Theory of Error-Correcting Codes
The aim of this unit is to provide you with an introduction to the theory of error-correcting codes employing the methods of elementary enumeration, linear algebra and finite fields.

Advanced Cipher Systems
Mathematical and security properties of both symmetric key cipher systems and public key cryptography are discussed, as well as methods for obtaining confidentiality and authentication.

Main project
The main project (dissertation) accounts for 25% of the assessment of the course and you will conduct this under the supervision of a member of academic staff.

Additional courses:
Applications of Field Theory
You will be introduced to some of the basic theory of field extensions, with special emphasis on applications in the context of finite fields.

Quantum Information Theory
‘Anybody who is not shocked by quantum theory has not understood it' (Niels Bohr). The aim of this unit is to provide you with a sufficient understanding of quantum theory in the spirit of the above quote. Many applications of the novel field of quantum information theory can be studied using undergraduate mathematics.

Network Algorithms
In this unit you will be introduced to the formal idea of an algorithm, when it is a good algorithm and techniques for constructing algorithms and checking that they work; explore connectivity and colourings of graphs, from an algorithmic perspective; and study how algebraic methods such as path algebras and cycle spaces may be used to solve network problems.

Advanced Financial Mathematics
In this unit you will investigate the validity of various linear and non-linear time series occurring in finance and extend the use of stochastic calculus to interest rate movements and credit rating;

Combinatorics
The aim of this unit is to introduce some standard techniques and concepts of combinatorics, including: methods of counting including the principle of inclusion and exclusion; generating functions; probabilistic methods; and permutations, Ramsey theory.

Computational Number Theory
You will be provided with an introduction to many major methods currently used for testing/proving primality and for the factorisation of composite integers. The course will develop the mathematical theory that underlies these methods, as well as describing the methods themselves.

Complexity Theory
Several classes of computational complexity are introduced. You will discuss how to recognise when different problems have different computational hardness, and be able to deduce cryptographic properties of related algorithms and protocols.

On completion of the course graduates will have:
- knowledge and understanding of: the principles of communication through noisy channels using coding theory; the principles of cryptography as a tool for securing data; and the role and limitations of mathematics in the solution of problems arising in the real world

- a high level of ability in subject-specific skills, such as algebra and number theory

- developed the capacity to synthesise information from a number of sources with critical awareness

- critically analysed the strengths and weaknesses of solutions to problems in applications of mathematics

- the ability to clearly formulate problems and express technical content and conclusions in written form

- personal skills of time management, self-motivation, flexibility and adaptability.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The examinations in May/June count for 75% of the final average and the dissertation, which has to be submitted in September, counts for the remaining 25%.

Employability & career opportunities

Our students have gone on to successful careers in a variety of industries, such as information security, IT consultancy, banking and finance, higher education and telecommunication. In recent years our graduates have entered into roles including Principal Information Security Consultant at Abbey National PLC; Senior Manager at Enterprise Risk Services, Deloitte & Touche; Global IT Security Director at Reuters; and Information Security Manager at London Underground.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

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Research profile. The Reid School of Music offers an exciting research environment that combines the theory, history, composition and practice of music with the scientific study of sound. Read more

Research profile

The Reid School of Music offers an exciting research environment that combines the theory, history, composition and practice of music with the scientific study of sound. We engage with a broad range of genres and traditions, including classical and popular music, Western and non-Western music, professional and amateur music making and music for screen. Our research is highly interdisciplinary, with centres and groups spanning other Colleges and Departments within the University of Edinburgh, from Physics and Neuroscience to Informatics, the Humanities, Divinity and the Social Sciences.

We have a large community of postgraduate students undertaking independent research in music.

If you are interested in undertaking a small independent research project in music, the 12-month MSc by Research is ideal. This programme is offered in any area served by the expertise of our music staff. In consultation with your supervisor you will develop an individual programme of coursework and research training over two semesters. You will submit a dissertation, or portfolio of projects equivalent to 30,000 words.

Candidates for larger-scale, doctoral research are normally admitted as probationary students for the first year of study, and on satisfactory completion of this first year are approved for registration for either MPhil (normally two years full-time, dissertation of 60,000 words) or PhD (maximum four years full-time, dissertation of 80,000–100,000 words).

All our research degrees may be studied part-time (for example, MSc by Research may be studied part-time over two years).

Staff have a wide range of research interests, engaging in research clustered around four main themes:

  • Music, Sound and Technology, including musical acoustics and organology
  • Musical Practice, including composition (electroacoustic, algorithmic, computer music and music for screen), and historical and contemporary performance research
  • Music and the Human Sciences, including music psychology and cognition, and music in the community
  • Music and Social Institutions, including 19th and 20th century musicology, popular music, and music sociology

Some of our current hubs of research activity include:

  • Acoustics and Audio Group
  • ECA Digitals
  • Edinburgh University Collection of Historic Musical Instruments
  • Institute for Music in Human and Social Development
  • Live Music Exchange

Please consult our staff profile pages to see our interests and availability; you may propose projects in any area for consideration.

Training and support

All of our research students benefit from ECA’s interdisciplinary approach and all are assigned two research supervisors. Your second supervisor may be from another discipline within ECA, or from somewhere else within the College of Arts, Humanities & Social Sciences or elsewhere within the University, according to the expertise required. On occasion more than two supervisors will be assigned, particularly where the degree brings together multiple disciplines.



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Programme description. This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world. Read more

Programme description

This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world.

Our research draws on neuroscience, cognitive science, linguistics, computer science, mathematics, statistics and psychology to span knowledge representation and reasoning, the study of brain processes and artificial learning systems, computer vision, mobile and assembly robotics, music perception and visualisation.

We aim to give you practical knowledge in the design and construction of intelligent systems so you can apply your skills in a variety of career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

Compulsory courses:

  • Informatics Research Review
  • Informatics Research Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses:

  • Intelligent Robotics
  • Agents, Knowledge and Data
  • Machine Learning
  • Natural Language Processing

You can choose from a variety of optional courses including:

  • Advanced Vision
  • Algorithmic Game Theory and Its Applications
  • Computer Animation and Visualisation
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Robotics: Science and Systems
  • Human-Computer Interaction
  • Software Architecture, Process and Management
  • Text Technologies for Data Science
  • Computational Cognitive Neuroscience

Career opportunities

Our students are well prepared for both employment and academic research. The emphasis is on practical techniques for the design and construction of intelligent systems, preparing graduates to work in a variety of specialisms, from fraud detection software to spacecraft control.



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Programme description. This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet. Read more

Programme description

This MSc will give you specialist knowledge in the design, implementation and use of computing systems ranging from the components of a single processor to computer networks as vast as the internet.

You will gain a solid foundation in theoretical understanding and learn a wide variety of practical techniques that you could use in varied career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses. The specialist areas are:

  • Analytical and Scientific Databases
  • Computer Systems, Software Engineering, and High Performance Computing
  • Programming Languages
  • Theoretical Computer Science
  • Cyber Security and Privacy

Compulsory courses:

  • Informatics Research Review
  • Informatics Research Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

There are more than 50 optional courses to choose from, such as:

  • Machine Learning and Pattern Recognition
  • Probabilistic Modelling and Reasoning
  • Extreme Computing
  • Bioinformatics
  • Computer Graphics
  • Computer Networking
  • Human-Computer Interaction
  • Parallel Architectures
  • Parallel Programming Languages and Systems
  • Software Architecture, Process and Management
  • Algorithmic Game Theory and its Applications
  • Computer Algebra
  • Computational Complexity

Career opportunities

Through this programme you will develop specialist, advanced skills in the development, construction and management of advanced computer systems.

You will gain practical experience and a thorough theoretical understanding of the field making you attractive to a wide range of employers or preparing you for further academic study.



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* Subject to validation, 2017 entry. Liverpool Hope’s MSc Computer Science is a research-informed, academically rigorous course and is designed to provide a flexible, purposeful and challenging set of coherent courses to meet scientific, industrial and employment challenges in this fast-evolving technological area. Read more
* Subject to validation, 2017 entry

Liverpool Hope’s MSc Computer Science is a research-informed, academically rigorous course and is designed to provide a flexible, purposeful and challenging set of coherent courses to meet scientific, industrial and employment challenges in this fast-evolving technological area. Graduates will have developed scientific and analytical skills which are highly valued in the computing, engineering, IT and business industries.

The course offers a mix of compulsory and elective courses, and a research dissertation, so you can focus your skill base and your potential career direction.

The course has been designed with employability in mind, whether it is within IT industry or as a function of other sectors, scientific computing and technical skills are in great demand and therefore highly valued. There are opportunities for placements and enterprise development.

Curriculum

The MSc Computer Science combines academic and practical course, consisting of eight taught courses (four compulsory and four elective) and a dissertation (final research project).

The Compulsory courses are:

· Computational Modelling and Simulation

· Algorithms

· Innovations in Computer Science

· Research Methods for Computer Science

· Dissertation for MSc Computer Science

Elective courses include:

· Embedded Systems and Robotics

· Cloud Computing and Web Services

· Mobile and Ubiquitous Computing

· Human Computer Interaction

· E-Business

Course Descriptions

· Computational Modelling and Simulation (compulsory – 15 credits): This course develops understanding and knowledge of the principles, techniques and design of computational modelling and their applications.

· Algorithms (compulsory - 15 credits): This course gives a firm grounding in the philosophy and evolution of algorithmic design and analysis for computer science, engineering and information systems.

· Innovations in Computer Science (compulsory - 15 credits): You will examine the particular research interests of Computer Science Department.

· Research Methods for Computer Science (compulsory - 15 credits): The course will expose you to the established techniques of research and enquiry that are used to extend, create and interpret knowledge in computer science

· Embedded Systems and Robotics (elective - 15 credits): This course will examine the Robotics Operating System and robotic programming languages, such as Urbi.

· Cloud Computing and Web Services (elective - 15 credits): You will study the concepts behind the idea of cloud computing and web services and gain practical knowledge of Azure, the .Net framework and C#.

· Mobile and Ubiquitous Computing (elective - 15 credits): You will examine mobile phone OSs (Android) and Windows Phone 7. You will learn how to develop software for these devices using JavaFX and C#/Silverlight.

· Human Computer Interaction (elective - 15 credits): Human computer interaction (HCI) is the study of interaction between people and computers and is the most multi-disciplinary module available in the MSc Computer Science.

·
* E-Business (elective - 15 credits): E-business encompasses, and is more than, e-commerce. You will examine e-commerce technology, such as the internet and web-based technologies.

· Dissertation for MSc Computer Science (compulsory - 60 credits): This module will allow the students to develop a Masters level research project with the support of an academic supervisor.

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The MSc in Digital Systems Engineering is a one-year full-time taught course that makes extensive use of the knowledge and expertise from our well established Intelligent Systems and Nano-Science Research Group. Read more
The MSc in Digital Systems Engineering is a one-year full-time taught course that makes extensive use of the knowledge and expertise from our well established Intelligent Systems and Nano-Science Research Group.

It is intended to provide students with a good theoretical background and solid hands-on experience of the techniques used in modern digital systems design. Using FPGAs as a hardware platform and VHDL as a design language, the programme provides students with:
-A balanced picture of state-of-the-art digital systems design methods
-A sound theoretical and practical knowledge of digital devices, tools, data networks and operating systems
-The ability to learn new techniques to keep up-to-date with new developments in an industrial and/or research setting
-Experience of the use of industry-standard tools to make them attractive candidates for prospective employers in the field
-Experience of working within a group and of the important management skills required by industry
-Hands-on experience of the different stages of the design of a modern digital system, which will culminate in the construction of a complex device (for example, an FPGA-based MP3 player)

Course Content

The course aims to provide a broad-based introduction to state-of-the-art digital system design techniques and to provide a solid grounding in both theory and practice. It is suitable for students wishing to pursue a career in digital electronic industry and research.

[[Group Project
The aim of this substantial group project is to immerse the students in a life-like scenario of a company developing digital systems. The project will involve the design, construction and implementation of a complete FPGA-based digital system, providing students with practical experience of project management and team skills. The system will include both software (such as human-computer interface, low-level programming) and hardware (such as FPGA, A/D converters, communication interfaces) components. The project will culminate in the design and realisation of a printed circuit board hosting a FPGA interfaced to a variety of peripherals. Communication links allowing connection to a PC will enable the creation of a diverse range of multimedia, diagnostic or communication systems. Furthermore, at the end of the project, students will keep the boards they have designed, providing them with a complete FPGA development system, allowing them to further investigate digital systems design.

The project preparation will begin towards the end of the Autumn term when groups will be given a Quality Assurance manual, that will prepare the students to establish effective company policies, procedures and roles for group members, introducing the Quality Assurance processes applied to medium to large projects in industry.

In the Autumn term, a module on 'C Programming' will hone the students' skills required to effectively carry out the software components of the project. The module will provide a practical introduction to writing and running C programs as an example of a procedural programming language.

In the Spring term, the actual project will get under way. Groups of 4-6 students will be formed, assigned a target system to design, and provided with a budget. In this term, the students will prepare an implementation plan that will be followed for the remainder of the project. Detailed system specifications will be established and the budget allocated, taking into account the cost of components and off-the-shelf IP modules.

In the Summer term, the project will continue with the pre-implementation phase. Students will design a PCB with the components (FPGA, communication interfaces, displays, memories, etc.) defined in the system specifications. The design will be sent to fabrication and returned by the end of term. Along with the PCB design, the students will develop a block-level algorithmic description of the system to be implemented, defining the role of each component within the system and beginning the development of the software components of the system.

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Computer vision and imaging is the exciting science and technology of machines that see, concerned with building artificial systems that obtain information from images that are derived from a range of sources. Read more
Computer vision and imaging is the exciting science and technology of machines that see, concerned with building artificial systems that obtain information from images that are derived from a range of sources. This MSc in Computing with Vision and Imaging teaches you the skills necessary to undertake work in this ever-evolving field.

Why study at Dundee?

Computer vision and imaging is a rapidly expanding field with plenty of real-life applications and opportunities. Here at Dundee, we encourage a professional, inter-disciplinary and user-centred approach to computer systems design and production.

Application areas include:
controlling processes - e.g. an industrial robot or an autonomous vehicle
detecting events - e.g. for visual surveillance or people counting
organising information - e.g. for indexing databases of images and image sequences
modelling objects or environments - e.g. for industrial inspection
medical image analysis
topographical modelling

You will acquire skills in computer vision, inference, algorithmic underpinnings of computer vision systems, how images and signals are formed, filter, compressed and analysed, and how multiple images can be combined.

Throughout this course, you will also develop the necessary skills to undertake independent research and participate in proposal development and innovation - an excellent grounding for many future careers.

What's Great about studying at Dundee?

Research-led teaching:
Teaching at Dundee is research-led, meaning that the MSc programme benefits from association with cutting-edge research of international standard and its commercial applications.

We also have an active Computer Vision and Image Processing research group. Our Vision and Imaging students are involved in a number of http://www.computing.dundee.ac.uk/projects/vision/projects.php, and have been involved with a number of completed research projects like ACTIVE, a project concerning adaptive interfaces for the operation of secondary controls in motor vehicles using pointing gestures and virtual dashboards.

Links with industry

The School of Computing collaborates with, and has links to, companies such as IBM, NCR and Oracle.

Our facilities

You will have 24-hour access to our award winning and purpose-built Queen Mother Building. It has an unusual mixture of lab space and breakout areas, with a range of conventional and special equipment for you to use. It's also easy to work on your own laptop as there is wireless access throughout the building. Our close ties to industry allows us access to facilities such as Windows Azure and Teradata, and university and industry standard software such as Tableau for you to evaluate and use.

Postgraduate culture

The School of Computing maintains a friendly, intimate and supportive atmosphere, and we take pride in the fact that we know all of our students - you're far more than just a matriculation number to us. We have a thriving postgraduate department with regular seminars and guest speakers.

What you will study

You select seven taught modules, three per semester, during the period September-April. You will make module selections with your advisor.

Semester 1 (Sept-Dec):
Probabilistic Inference and Learning
Signals and Images

Plus two from:
Technology Innovation Management
Computer Graphics
Logical Inference & Symbolic Reasoning
Information Theory

Semester 2 (Jan-Mar):
Vision and Perception
Research Methods

Plus one from:
Computing Research Frontiers
Multi-agent Systems & Grid Computing

Subject to examination performance, you then progress to the MSc project which runs from May to September, or to a Diploma project lasting 9 weeks.

Please note that some of the modules in the programme are shared with other masters programmes and some of the teaching and resources may be shared with our BSc programme. These joint classes offer a valuable opportunity to learn from, and discuss the material with, other groups of students with different backgrounds and perspectives.

How you will be assessed

The taught modules are assessed by continuous assessment plus end of semester examinations in December and March/April. The project is assessed by dissertation.

Computing coursework is often very practical, e.g. writing computer programs, designing interfaces, writing reports, constructing web sites, testing software, implementing databases, analysing problems or presenting solutions to clients.

Careers

The knowledge, skills and understanding that you will gain in the areas of computer vision, inference and learning will enable you to work effectively in the application of video and image-based computing - whether you choose industry, commerce or research.

Computing at the University of Dundee is ranked 21st in the UK according to most recent Times Good University Guide and 12th in the UK according to the Guardian University League Table 2009. The University of Dundee has powered its way to a position as one of Scotland's leading universities with an international reputation for excellence across a range of activities. With over 18,000 students, it is growing fast in both size and reputation. It has performed extremely well in both teaching and research assessment exercises, has spawned a range of spin-out companies to exploit its research and has a model wider-access programme.

Dundee has been described as the largest village in Scotland which gives an indication of how friendly and compact it is. With a population of 150,000 it is not too large but has virtually all the cultural and leisure activities you would expect in a much larger city. It is situated beside a broad estuary of the river Tay, surrounded by hills and farmland, and for lovers of the great outdoors it is hard to imagine another UK location that offers so much all year round on land and water. The University is situated in the centre of Dundee, and everything needed is on the one-stop campus: study facilities, help, advice, leisure activities... yet the attractions of the city centre and the cultural quarter are just a stroll away.

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There is currently a worldwide shortage in graduates qualified in Bioinformatics and the skills to interpret the data that is going to underpin advances in biology and medicine in 21st Century. Read more
There is currently a worldwide shortage in graduates qualified in Bioinformatics and the skills to interpret the data that is going to underpin advances in biology and medicine in 21st Century. With the advent of Personalised Medicine, the demand for specialists in Computational Biology and Bioinformatics will further increase. This gives you the opportunity to build your transferable skill set across a range of cutting edge technologies and start building a career in this central facet of modern biology.

Students completing the MSc course in Bioinformatics and Computational Genomics will have the necessary skills and knowledge to undertake research and development in industry (Biotechnology, Pharmaceutical, Diagnostic companies), in medical research centres and in academic institutions worldwide.

Computational, statistical and machine learning methods form an integral part of modern research in Molecular Biology, Cell Biology, Pharmacology, Public Health Care and in Medicine. The past decade has seen enormous progress in the development of molecular and biomedical technologies. Today’s high-throughput array and sequencing techniques produce data in the range of terabytes on a daily basis and new technologies continuously emerge. This will further increase the stream of data available for biomedical research. For this reason analyzing, visualizing and managing this huge amount of data is a challenging task. The Queen’s MSc course in Bioinformatics and Computational Genomics targets these data-driven challenges of modern science. The course is open to graduates in computer science, life sciences, physics or statistics.

The programme will consist of an Introductory short course (two weeks) in Cell Biology, followed by modules in:

• Genomics & Genetics
• Analysis of Gene Expression
• Scientific Programming & Statistical Computing
• Algorithmic Biology
• Statistical Biology
• Bioimaging Informatics
• Research project : MSc dissertation

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This course is aimed at students with a strong interest in financial trading in integrated financial markets. It addresses the needs of students who are looking to pursue a career in global financial trading and related fields, such as financial analysis. Read more

OVERVIEW

This course is aimed at students with a strong interest in financial trading in integrated financial markets. It addresses the needs of students who are looking to pursue a career in global financial trading and related fields, such as financial analysis.

You will focus on trading and the behaviour of global financial markets through the use of an on-campus simulated Trading Floor, which provides practical exposure and hands-on experience in the art of trading. This course explores the principles of equity trading and evaluation, bond trading and financial derivatives. In addition, you will gain career-ready business skills sought after by employers, including teamwork, communication, presentation and leadership skills.

WHY CHOOSE THIS COURSE?

By successfully completing this course you will not only gain a master's qualification, but also be prepared for the Financial Information Associate Certificate, which is recognised by the world’s leading financial information companies. You will be taught by industry-trained academics and practitioners, including some who are chartered accountants, chartered financial analysts and financial risk managers. In addition, you will also have an opportunity to gain industry experience through field trips. Previous trips have included visits to New York, the Bank of England and London Stock Exchange.

MODULES

• Ethics and Quantitative Methods
• Understanding Financial Reporting and Analysis
• Trading Economics
• Global Financial Markets
• Valuation of Equity and Fixed Income
• Stochastic Finance
• Computational and Algorithmic Trading
• Empirical Finance and Accounting Research Methods
• Financial Derivatives Trading

Project options
• Internship
• Consulting Project
• Entrepreneurship Project
• Simulation
• Dissertation

START DATES

MSc Global Financial Trading has start dates in October 2017.

SCHOLARSHIP OPPORTUNITIES

Coventry University London is delighted to have recently launched a number of scholarships to UK and International students. You can find out more about our Scholarships by viewing our website.

FUTURE PROSPECTS?

“I had a fantastic experience at Coventry University London, studying with passionate and dedicated teachers, and an employability team always available to offer advice and support to help secure jobs and internships.” - Agathe Silvagni, France, Data Analyst at Bloomberg

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The Web Intelligence MSc aims to provide you with the knowledge and skills to solve challenging computational problems related to advanced reasoning systems for the internet. Read more

The Web Intelligence MSc aims to provide you with the knowledge and skills to solve challenging computational problems related to advanced reasoning systems for the internet. It will give you a broad understanding of web intelligence and a thorough knowledge of techniques for developing intelligent software. 

Key benefits

  • Located in central London giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS), and the Institution of Engineering and Technology (IET).
  • Opportunities to explore the fundamental roles and practical impacts of the use of artificial intelligence techniques in advanced computing.
  • Key study areas include fundamental internet technologies with complementary aspects of artificial intelligence, algorithmic issues on the web, and agents and multi-agent systems.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in web intelligence and related fields.
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Description

The Web Intelligence MSc will provide you with the practical knowledge and expertise to evaluate, design and build intelligent software for the internet. You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits, including 60 credits that will come from a research project and dissertation of 10,000 words. You will study Artificial Intelligence, Agents and Multi-agent Systems as well as Software Engineering of Internet Systems. There are also opportunities to explore a broad range of optional modules allowing you to develop a study pathway that reflects your interests.

Course purpose

A graduate in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will provide you with the practical knowledge and expertise to enable you to evaluate, design and build intelligent software for the web. Research for your individual project will provide valuable preparation for a career in research or industry.

Course format and assessment

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

You are expected to spend approximately 150 hours of effort (i.e. about 10 hours per credit) for each module you attend in your degree. These 150 hours cover every aspect of the module: lectures, tutorials, lab-based exercises, independent study based on personal and provided lecture notes, tutorial preparation and completion of exercises, coursework preparation and submission, examination revision and preparation, and examinations.

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project will be assessed through a dissertation. 

Career prospects

Our graduates have continued on to have very successful careers in industry and research. Recent employers have included general software consultancy companies, specific software development businesses and the IT departments of large institutions (financial, telecommunications and public sector). Some graduates have entered into the field of academic and industrial research in software engineering, bio-informatics, algorithms, artificial intelligence and computer networks.



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This highly specialised degree is designed to provide a practical understanding of a wide range of corporate finance services and corporate transactions. Read more

This highly specialised degree is designed to provide a practical understanding of a wide range of corporate finance services and corporate transactions. Both, corporate financial management and investment banking is at the core of the programme which is highly regarded in the City of London. 

Through hands-on sessions and extensive use of case-studies and financial analysis simulations, participants will be fascinated by the exciting world of venture capital, private equity, corporate governance and mergers and acquisitions. You will specialise in corporate investment and capital budgeting decisions, IPOs, payout policy, capital structure, enterprise valuation, financial analysis and risk management. You will also gain an in-depth understanding of financial markets, securities trading and quantitative techniques, and be able to further specialise on a wide range of additional elective topics.

MSc Corporate Finance graduates have the advantage of exemption from the Corporate Investment exam of its CFC qualification.

Highlights

  • Study one of the most reputable Masters within the investment banking community
  • Focus on highly specialised topics such as private equity, corporate governance and mergers and acquisitions.
  • Experience a practice-centred delivery approach including hands-on sessions, case studies, financial analysis simulations and programming sessions.
  • Benefit from professional exam exemptions from the CFC qualification.
  • Choose from over 15 elective modules to gain specialisation in a wide array of finance topics

Course structure

October – December: Part 1 Autumn Term

January: Part 1 Exams

January-April: Part 2 Spring Term

May – June: Part 2 Exams

June – August (12 month programme only): Part 3

August/Sep (12 month programme only): Part 3 Coursework deadlines

Course content

Part 1 compulsory modules

Part 2 compulsory modules

Part 2 optional modules

Students on the 9-month (12-month) programme can select 80 (60) credits of electives from the following list

A minimum of 40 of those credits must be chosen from the following:

Part 3 optional modules

Students on the 12-months programme should take 20 credits from the following:

Learning options

Full-time: 9 months Full-time: 12 months

Students will be resident and undertake full-time study in the UK. Under both, the 9 and 12-month programmes students take compulsory and/or elective modules in Part 2.

The 12 month option involves taking an elective 20 credit module between July and August, which would also mean a 20 credit reduction in the number of taught modules taken in the spring term.

Careers

There is a demand for professionals who combine an understanding of the financial markets with knowledge of the financial decisions facing companies in their day-to-day operations. Such professionals also need a clear insight into related fields including accounting, risk management, capital budgeting, debt and equity finance, financial planning, venture capital and mergers and acquisitions.

As a MSc Corporate Finance graduate, you will be well equipped to join careers in investment banks in the City of London and other international financial centres, professional services firms, including management consultancies and accountancy practices, and small, entrepreneurial ventures where an in-depth knowledge of finance will be of direct benefit to the owner/managers seeking to build their business.

Professional accreditation

CISI Diploma

The ICMA Centre is a Chartered Institute of Securities and Investment (CISI) Centre of Excellence. Centres of Excellence are a select group of UK universities, recognised by the CISI as offering leadership in academic education on financial markets. Students who are on a financially-related masters course recognised by the CISI are eligible for exemptions and membership. 

ICMA Centre students who register and successfully complete two CISI Diploma in Capital Markets modules (Securities and Bonds & Fixed Interest Markets) are eligible for an exemption from the third module (Financial Markets).

NDRCTC CFC Certificate

Students are eligible for exemption from the Corporate Investment exam. This will apply to graduates from 2011 entry onwards. (The CFC qualification comprises 3 exams: Overview and fundamentals of corporate finance; Corporate investment; Corporate financing)



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