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This MSc programme focuses on the development of sophisticated computer graphics applications and on the development of tools commonly used in the creation of content for these applications. Read more
This MSc programme focuses on the development of sophisticated computer graphics applications and on the development of tools commonly used in the creation of content for these applications. It provides students with opportunity to develop important skills necessary for employment in this sector. They will use their expertise to, for example, develop interactive graphical scenes and deploy up to date techniques to implement real-time and offline visual effects.

Course Overview

This programme will equip students with skills at a high academic level and also crucially enable them to practically implement their knowledge because of the ‘hands-on’ emphasis of the programme.

The main themes of the programme are:
-Current and emerging algorithms and techniques used in film visual effects and games programming
-Approaches used to generate off-line visual effects
-Approaches used to generate real-time interactive games

The first theme develops in the student the necessary skills required to implement algorithms and techniques used to generate realistic scenes. These concepts will be explored in detail.

The second theme addresses the need for students to identify, evaluate and implement suitable methods to solve specific problems related to creating off-line visual effects.

The third theme recognises the need to solve these problems using approaches optimised for real-time computer games development and develops in the student the requisite skills.

Modules

-Animation Systems Development (20 credits)
-Artificial Intelligence for Games & VFX (20 credits)
-GPU Shader Development (20 credits)
-Leadership and Management (20 credits)
-Research Methods and Data Analysis (20 credits)
-Visual Simulation (20 credits)
-Major Project (60 credits)

Key Features

Applicants for this programme will have an interest in computer graphics and Computer Generated Imagery (CGI). The main themes of the programme are current and emerging algorithms and techniques used in film visual effects and games programming, approaches used to generate off-line visual effects and approaches used to generate real-time interactive games. This also includes the development/enhancement of tools used in the CGI and animation industry. Graduates will be concerned with the discipline of developing software and applications using high level programming languages. They will also be experienced in creating custom animated scenes using the powerful scripting languages of industry standard applications such as Maya and Houdini software. Graduates will have an advanced understanding of computer graphics, GPU shader development, and visual simulation methods making use of modern artificial intelligence and simulation techniques. Graduated are likely to find employment either within the film VFX industry, computer games or traditional software engineering sectors.

Assessment

An Honours Degree (2.2 or above) or advanced qualification in Computer Science or cognate discipline from a UK University or recognised overseas institution, or industrial experience in Computer Networking and an Honours Degree.

Where English is not your first language, we ask that you hold an Academic IELTS test with a score of at least 6.0 (no element less than 5.5) or TOEFL with a minimum score of 550 (213 for computer based test).

Career Opportunities

It is expected that graduates would seek positions such as:
-Software Engineers
-Senior Software Engineers
-App Developers
-CGI Special Effects Programmers
-Games Programmers
-Lead Programmers
-Render Manager
-VFX Programmer
-VFX Technical Directors

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Improve your employment prospects and accelerate your career with our cutting-edge postgraduate qualification aimed specifically at non-computing graduates and experienced professionals. Read more
Improve your employment prospects and accelerate your career with our cutting-edge postgraduate qualification aimed specifically at non-computing graduates and experienced professionals. Equip yourself with the computational tools and skills required to address strategic problems in your area of expertise and make your move into the growing, international, high-value IT industry.

Key features

-Structure: This programme will give you knowledge of computational problem solving, computer technology and software development with a focus on human-computer-interaction and usability as competitive factors. The programme includes a CS workshop module that guarantees that you will collaborate with experts from our world-leading research centres.
-Resources: Benefit from easy access to cutting-edge specialist labs and next-generation software and hardware on a single-campus. You will benefit directly from facilities such as our NVIDIA sponsored GPU Research Centre and our High-Performance Computing Centre. You will be provided with a personal (free) iPad mini enabling you to fully take part of our electronically enhanced teaching.
Financial support: Plymouth University offers a range of general and merit-based postgraduate scholarships for local and international students including GREAT scholarships for students of Indian nationality. To be considered for one of these scholarships you must first hold a conditional offer of a place on a postgraduate taught (PGT) degree programme.
-Careers: A post-graduate qualification in computer science combined with a background in a non-computing field opens the door to a wide range of careers including Systems Analyst (start £20-25K, senior £40K+), Information Security or Multimedia Specialist (start £20-25K, senior £35-60K), Operational Researcher (start £20-28K, senior £40-100K+) and IT consultant (starting salary £20-30K, senior salary £40-80K) . With the recognised skill gap in the IT sector, currently, 85 per cent of computer science students find employment within six months of finishing their programme.
-Lifestyle: Work hard and play hard in Britain’s Ocean City with its beautiful moors and beaches and its historical naval links. The City of Plymouth is located in the county of Devon, repeatedly selected as the best place to live in the UK. Find out more about life in Plymouth and the South West.
-Quality: As one of UK’s ten largest universities, Plymouth combines the best of modern and traditional higher education, with friendly and approachable professors and a world-leading research profile in future-focused areas such as medicine, cognitive science, environmental science and robotics.

Course details

Semester 1 modules
-Computational Problem Solving and Computer Systems
-Software Development and Databases
-Computer Networks and Cybersecurity

Semester 2 modules
-HCI, Web and Mobile Development
-Software Project Management (including group project)
-Computer Science Workshops

Individual project
-The taught element of the programme is followed by an individual project.

Core modules
-ISAD515 Computational Problem Solving and Computer Systems
-NET505 Computer Networks and Cybersecurity
-PROJ516 MSc Project
-SOFT562 Software Development and Databases
-SOFT549 HCI, Web and Mobile Development
-AINT514 Computer Science Workshop
-ISAD516 Software Project Management

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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Why Study Financial Computing?. Financial institutions are under considerable pressure to increase their computational capabilities. Read more
Why Study Financial Computing?
Financial institutions are under considerable pressure to increase their computational capabilities. This is the result of increased regulatory requirements, new electronic and algorithmic trading channels as well as increased competition for speed and accuracy. This critical capability is delivered by a combination of mathematics, technology and finance.

As a result there is growing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

This unique programme provides numerate graduates with the expertise to develop a professional career in this profitable and intellectually exciting field. It has been designed to match the requirements of top employers in the industry.

Access to Expertise
The MSc in Financial Computing is directed and has been designed by Dr Sebastian del Bano Rollin former Global Head of FX Quantitative Research at Citigroup amongst other senior roles in the financial industry.

Get Industry Experience
The Financial Computing MSc can be enhanced with a one year industry placement that will allow you to gain valuable industry expertise.

Our Scholarships
We reward your academic excellence with scholarships for our MSc Financial Computing. This year we will be awarding five tuition fee scholarships of £5,000 each for outstanding graduates with degrees equivalent to a 2:1 or above.

The Programme
The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed both at science graduates with some experience in programming as well as engineering graduates with some mathematical exposure. The content of the programme is a combination of technology and applied financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance computing and GPU development. If you are studying full time with us, you will complete eight taught modules as well as completing a 10,000 word dissertation over the academic year. To view further information about the content and structure of our programme visit: http://www.qmul.ac.uk/postgraduate/taught/coursefinder/courses/155455.html

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This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Full time students will take four modules per semester as well as completing a 10,000 word dissertation. There are also pre-sessional modules in mathematics and financial markets providing a good opportunity for students to catch up with the necessary prerequisite knowledge.

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Mathematical finance is an area of applied mathematics where concepts and techniques that lie close to the heart of pure mathematics are applied routinely to solve a great variety of important practical problems arising in the day-to-day business of the world's financial institutions. Read more

About the course

Mathematical finance is an area of applied mathematics where concepts and techniques that lie close to the heart of pure mathematics are applied routinely to solve a great variety of important practical problems arising in the day-to-day business of the world's financial institutions.

The objective of the Brunel MSc in Financial Mathematics is to guide students through to a mastery of the sophisticated mathematical ideas underlying modern finance theory, along with the associated market structures and conventions, with emphasis on:

- The modelling of the dynamics of financial assets, both in equity markets and in fixed-income markets
- The pricing and hedging of options and other derivatives, and
- The quantification and management of financial risk.

Candidates are also provided with the means to master the numerical and computational skills necessary for the practical implementation of financial models, thus enabling you to put theory into practice and putting you in a good position to carry out work for a financial institution. We therefore offer a programme that provides a balanced mixture of advanced mathematics (including modern probability theory and stochastic calculus), modern finance theory (including models for derivatives, interest rates, foreign exchange, equities, commodities, and credit), and computational technique (GPU-based high-performance computing).

The MSc in Financial Mathematics offers a range of exciting modules during the Autumn and the Spring terms, followed by an individual research project leading to a dissertation that is completed during the Summer term.

Aims

Financial mathematics is a challenging subject, the methods of which are deployed by sophisticated practitioners in financial markets on a daily basis. It builds on the application of advanced concepts in modern probability theory to enable market professionals to tackle and systematically resolve a huge range of issues in the areas of pricing, hedging, risk management, and market regulation. The main objective of the Brunel MSc in Financial Mathematics is to provide candidates with the knowledge they need to be able to enter into this exciting new area of applied mathematics and to position themselves for the opportunity to work in financial markets.

Among the main distinguishing features of our programme are the following:

We aim to teach the key ideas in financial asset pricing theory from a thoroughly modern perspective, using concepts and methods such as pricing kernels, market information filtrations, and martingale techniques, as opposed say to the more traditional but old-fashioned approach based on the historical development of the subject.

In our programme candidates are asked at each stage to undertake a critical re-examination of the hypotheses implicit in any financial model, with a view to gaining a clear grasp of both its strengths and its limitations.

The programme includes courses on high-performance computing that provide candidates with the techniques whereby financial models can be implemented.

Course Content

Programme structure

The programme offers five "compulsory" modules, taken by all candidates, along with a variety of elective modules from which students can pick and choose. There are lectures, examinations and coursework in eight modules altogether, including the five compulsory modules. Additionally, all students complete an individual research project on a selected topic in financial mathematics, leading to the submission of a dissertation.

Compulsory modules:

Probability and stochastics
Financial markets
Option pricing theory
Interest rate theory
Financial computing I

Elective Modules:

Portfolio theory
Information in finance with application to credit risk management
Mathematical theory of dynamic asset pricing
Financial computing II
Statistics for Finance
Financial Mathematics Dissertation

Special Features

The Department of Mathematics, home to its acclaimed research centre CARISMA, has a long tradition of research and software development, in collaboration with various industry partners, in the general area of risk management.

The Department is a member of the London Graduate School in Mathematical Finance, which is a consortium of mathematical finance groups of Birkbeck College, Brunel University London, Imperial College London, King’s College London, London School of Economics, and University College London. There is a strong interaction between the financial mathematics groups of these institutions in the greater London area, from which graduates can benefit. In particular there are a number of research seminars that take place regularly throughout the year which students are welcome to attend.

Assessment

Assessment is by a combination of coursework, examination, and dissertation. Examinations are held in May. The MSc degree is awarded if the student reaches the necessary overall standard on the taught part of the course and submits a dissertation that is judged to be of the required standard. Specifically, to qualify for the MSc degree, the student must: (a) take examinations in eight modules including the four compulsory modules, (b) attain the minimum grade profile (or better) required for a Masters degree and (c) submit a dissertation of the required standard. If a student does not achieve the requirements for the degree of MSc, they may, if eligible, be awarded a Postgraduate Diploma.

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This course is suitable for numerate graduates across many disciplines. Non-computing graduates are eligible. You will learn how to use state-of-the-art computer science methods to process a range of data, including (but not limited to) big data. Read more
This course is suitable for numerate graduates across many disciplines. Non-computing graduates are eligible.

You will learn how to use state-of-the-art computer science methods to process a range of data, including (but not limited to) big data. You will develop technical, statistical, analytical and data mining skills. The course incorporates methods of statistical analysis and data mining to extract understanding from data, formulate high-quality data models and interpret them to ‘tell a story’. You will learn how to communicate these effectively to stakeholders, bearing in mind ethical, legal and societal implications.

You will be introduced to data science concepts, techniques and algorithms for processing and visualising datasets so as to infer useful, actionable knowledge.

Features and benefits of the course

-The School has an extensive range of equipment in our own specialist laboratories which is supported by a dedicated team of technical staff.
-Research in the School was rated 'internationally excellent' with some rated 'world-leading' in the 2014 Research Excellence Framework (REF).
-Our online virtual learning platform Moodle, provides access to lectures, course materials and assessment information.
-Classes are concentrated on certain days of the week to facilitate part-time students’ attendance and allow full-time students to undertake part-time employment if necessary.
-The School of Computing, Mathematics and Digital Technology is a member of the Oracle Academy.
-We are an academic partner of the Institute of Information Security Professionals (IISP). This partner status recognises our expertise in the field of information and cyber security.
-We are also an Academy of the Computer Technology Industry Association (CompTIA) and deliver their partner programme which provides a pathway for students towards a rewarding, high-growth IT career.

Placement options

Some students undertake practical work for their projects while working in organisations which have offered placement opportunities.

About the Course

The School has an extensive range of equipment in our own specialist laboratories which are supported by a dedicated team of technical staff, including GPU clusters to support big data processing.

Classes are concentrated on certain days of the week to facilitate part-time students’ attendance and allow full-time students to undertake part-time employment if necessary.

Your individual project will investigate a challenging but constrained data science problem. The project will involve performing an end-to-end science task pipeline including data collection, formulation of one or more questions to be asked about the data, typical preprocessing steps, for example, cleaning, transforming and exploring, analysis, applicable learning methods, modelling, visualisation, interpretation and assessment of models.

Assessment details

Assessment will be through coursework, examination and dissertation.

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This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.

You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.

You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.

We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

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This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.

You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.

You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.

We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Read less
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance. Read more
This unique programme provides numerate graduates with the requisite expertise for the development of a professional career in the profitable and intellectually exciting triangle formed by mathematics, technology and finance.

Financial institutions rely on a functional blend of Mathematics, Technology and Finance to develop, enhance and sustain their competitive edge. The financial industry is undergoing a second wave of technological transformation related in particular to
: the establishment of electronic trading platforms; improved risk management and pricing accuracy; the high performance computing implications of expanding regulatory requirements.

As a result there is increasing demand for numerate and technologically capable personnel from a wide range of top employers including investment banks, hedge funds, financial software companies, brokerage firms and consultancy firms. Other business lines are now developing similar paradigms where numerate, technologically able personnel are part of business innovation and decision-making.

The Financial Computing MSc is run jointly by the School of Mathematical Sciences and the School of Electronic Engineering and Computer Science. It is aimed at science and engineering graduates with mathematical exposure and some experience in computer programming. The content of the programme is a combination of technology and financial mathematics. It contains modules related to up-to-the-minute industry challenges such as high performance and GPU development.

Why study with us?

Queen Mary is a member of the prestigious Russell Group of leading UK universities, combining world-class research and teaching excellence.

You will be taught by distinguished academics and experienced practitioners who blend advanced theory with practical applications.

You will study in recently refurbished MSc student offices, with state-of-the-art computers and software.

We are conveniently located in central London, in close proximity to the two world renowned financial districts of the City of London and Canary Wharf.

Read less
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017). Read more

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.

Key Features of the MSc Data Science

The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.

The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.

Modules

Modules for the MSc Data Science programme include:

- Visual Analytics

- Data Science Research Methods and Seminars

- Big Data and Data Mining

- Big Data and Machine Learning

- Mathematical Skills for Data Scientists

- Data Visualization

- Human Computer Interaction

- High Performance Computing in C/C++

- Graphics Processor Programming

- Computer Vision and Pattern Recognition

- Modelling and Verification Techniques

- Operating Systems and Architectures

Facilities

The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.

As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.

Career Destinations

- Data Analyst

- Data mining Developer

- Machine Learning Developer

- Visual Analytics Developer

- Visualisation Developer

- Visual Computing Software Developer

- Database Developer

- Data Science Researcher

- Computer Vision Developer

- Medical Computing Developer

- Informatics Developer

- Software Engineer



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