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The Computer Animation Master’s programme at Kent is oriented towards current industrial needs, technology and practice. It is designed to be a direct route into this high-profile, modern and creative industry, and has been developed jointly by the School and our industrial partner Framestore CFC. Read more
The Computer Animation Master’s programme at Kent is oriented towards current industrial needs, technology and practice. It is designed to be a direct route into this high-profile, modern and creative industry, and has been developed jointly by the School and our industrial partner Framestore CFC.

Develop your knowledge and understanding of the animation process, software tools, techniques and packages, and the technical aspects of working in a professional animation environment. The MSc programme offers invaluable experience of working to professional briefs and under expert supervision of professional animators to prepare you for a career in industry.

Competition is fierce in animation and visual effects and success depends on your concentration levels, constant practise and ability to grasp the essence and modern techniques of animation. Successful former students are now working in animation and animation layout roles for companies such as Sony Games and Framestore CFC on major titles in games, television and film.

Visit the website https://www.kent.ac.uk/courses/postgraduate/248/computer-animation

About the School of Engineering and Digital Arts

The School of Engineering and Digital Arts successfully combines modern engineering and technology with the exciting field of digital media. The School, which was established over 40 years ago, has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. We have a thriving student population studying for postgraduate degrees in a friendly, supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Course structure

This intensively taught postgraduate course lasts a full year. It takes place in a dedicated computer laboratory where you have your own seat and computer for the duration of the course. The course lectures and workshops, whether led by visiting professionals or staff, are all held in this room. Demonstrations and showing of films are by means of an HD projector. By the end of the year, the lab will be where you live as much as your accommodation.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

EL831 - Digital Visual Art set-up (15 credits)
EL832 - Animation Principles (15 credits)
EL833 - Visual Training (15 credits)
EL837 - Professional Group Work (15 credits)
EL863 - Advanced 3D Modelling (15 credits)
EL864 - Pre-Visualisation (15 credits)
EL865 - Action in Animation (15 credits)
EL866 - Acting in Animation (15 credits)
EL830 - Computer Animation Project (60 credits)

Assessment

Each module is assessed by practical assignments. The project work is assessed on the outcome of the project itself.

Programme aims

This programme aims to:

- enable you to develop your knowledge and understanding within the field of 3D computer animation, which will equip you to become a professional in the animation and visual effects industry

- produce professionally-trained animators who are highly skilled in using state-of-the-art 3D animation software for producing animated films

- provide you with proper academic guidance and welfare support

- create an atmosphere of co-operation and partnership between staff and students, and offer you an environment where you can develop your potential

- strengthen and expand opportunities for industrial collaboration with the School of Engineering and Digital Arts.

Research areas

- Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

Careers

We have developed the programme with a number of industrial organisations, which means that successful students will be in a strong position to build a long-term career in this important discipline.

The School of Engineering and Digital Arts (http://www.eda.kent.ac.uk/) has an excellent record of student employability (http://www.eda.kent.ac.uk/school/employability.aspx). We are committed to enhancing the employability of all our students, to equip you with the skills and knowledge to succeed in a competitive, fast-moving, knowledge-based economy.

Graduates who can show that they have developed transferable skills and valuable experience are better prepared to start their careers and are more attractive to potential employers.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. Read more
The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. The School enjoys an international reputation for its work and prides itself in allowing students the freedom to realise their maximum potential.

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

We undertake high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Visit the website https://www.kent.ac.uk/courses/postgraduate/262/electronic-engineering

Project opportunities

Some projects available for postgraduate research degrees (http://www.eda.kent.ac.uk/postgraduate/projects_funding/pgr_projects.aspx).

Research areas

- Communications

The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

- photonic components
- networks/wireless systems
- microwave and millimetre-wave systems
- antenna systems
- radio-over-fibre systems
- electromagnetic bandgaps and metamaterials
- frequency selective surfaces.

- Intelligent Interactions:

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

- Instrumentation, Control and Embedded Systems:

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

- monitoring and characterisation of combustion flames
- flow measurement of particulate solids
- medical instrumentation
- control of autonomous vehicles
- control of time-delay systems
- high-speed architectures for real-time image processing
- novel signal processing architectures based on logarithmic arithmetic.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. Read more
The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. The curriculum is very flexible. Students can compile their individual study plans based on their background and interests. It is also a very practical program. In addition to lectures and tutorials, students will complete two seminars, one or two projects and the master thesis.

In the beginning students will choose one or two key courses. Key courses are courses which introduce the students to the research areas represented at the Department of Computer Science. The following key courses are offered:

• Algorithm Theory
• Pattern Recognition
• Databases and Information Systems
• Software Engineering
• Artificial Intelligence
• Computer Architecture

After that, students can specialize in one of the following three areas:

• Cyber-Physical Systems
• Information Systems
• Cognitive Technical Systems

Here are some examples of subjects offered in the three specialization areas:

Cyber-Physical Systems:

• Cyber-Physical Systems – Discrete Models
• Cyber-Physical Systems – Hybrid Control
• Real Time Operation Systems and Reliability
• Verification of Embedded Systems
• Test and Reliability
• Decision Procedures
• Software Design, Modeling and Analysis in UML
• Formal Methods for Java
• Concurrency: Theory and Practice
• Compiler Construction
• Distributed Systems
• Constraint Satisfaction Problems
• Modal Logic
• Peer-to-Peer Networks
• Program Analysis
• Model Driven Engineering

Information Systems:

• Information Retrieval Data Models and Query Languages
• Peer-to-Peer Networks
• Distributed Storage
• Software Design, Modeling and Analysis in UML
• Security in Large-Scale Distributed Enterprises
• Machine Learning
• Efficient Route Planning
• Bioinformatics I
• Bioinformatics II
• Game Theory
• Knowledge Representation
• Distributed Systems

Cognitive Technical Systems:

• Computer Vision I
• Computer Vision II
• Statistical Pattern Recognition
• Mobile Robotics II
• Simulation in Computer Graphics
• Advanced Computer Graphics
• AI Planning
• Game Theory
• Knowledge Representation
• Constraint Satisfaction Problems
• Modal Logic
• Reinforcement Learning
• Machine Learning
• Mobile Robotics I

We believe that it is important for computer science students to get a basic knowledge in a field in which they might work after graduation. Therefore, our students have the opportunity to complete several courses and/or a project in one of the following application areas:

• Bioinformatics
• Educational Sciences
• Geosciences
• Cognitive Sciences
• Mathematics
• Medicine
• Meteorology
• Microsystems Engineering
• Physics
• Political Sciences
• Psychology
• Sociology
• Economics

In the last semester, students work on their master’s thesis. They are expected to tackle an actual research question in close cooperation with a professor and his/her staff.

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Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries. Read more

Medical imaging is a rapidly-growing discipline within the healthcare sector, involving clinicians, physicists, computer scientists and those in IT industries.

This programme delivers the expertise you'll need to forge a career in medical imaging, including radiation physics, image processing, biology, computer vision, pattern recognition, artificial intelligence and machine learning.

Programme structure

This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and an extended project.

Example module listing

The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.

Facilities, equipment and support

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab.

The Department’s student common room is also covered by the university’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices. There is also a Faculty quiet room for individual study.

We pride ourselves on the many opportunities that we provide to visit collaborating hospitals. These enable you to see first-hand demonstrations of medical imaging facilities and to benefit from lectures by professional practitioners.

To support material presented during the programme, you will also undertake a selection of ultrasound and radiation detection experiments, hosted by our sister MSc programme in Medical Physics.

Educational aims of the programme

The taught postgraduate Degree Programmes of the Department are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant).

To fulfil these objectives, the programme aims to:

  • Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing & Communications, from the UK, Europe and overseas
  • Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
  • Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
  • Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
  • Provide a high level of flexibility in programme pattern and exit point
  • Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Technical characteristics of the pathway

Medical Imaging is a rapidly growing discipline within the healthcare sector, incorporating engineers, physicists, computer scientists and clinicians. It is driven by the recent rapid development of 3-D Medical Imaging Systems, fuelled by an exponential rise in computing power.

New methods have been developed for the acquisition, reconstruction, processing and display of digital medical-image data with unprecedented speed, resolution and contrast.

This programme in Medical Imaging is aimed at training graduates for careers in this exciting multi-disciplinary area, and our graduates can expect to find employment in the medical imaging industry or the public health care sector.

It represents a blend of fundamental medical physics topics concerned with image acquisition and reconstruction coupled with imaging science and image engineering topics such that graduates understand how images are formed and how advanced machine-based methods can be bought to bare to provide new diagnostic information.

Global opportunities

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.



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The School conducts high-quality significant national and international research and offers excellent opportunities for graduate studies, successfully combining modern engineering and technology with the exciting field of digital media. Read more
The School conducts high-quality significant national and international research and offers excellent opportunities for graduate studies, successfully combining modern engineering and technology with the exciting field of digital media. The digital media group has interests in many areas of interactive multimedia and digital film and animation.

Visit the website https://www.kent.ac.uk/courses/postgraduate/264/digital-arts

About the School of Engineering and Digital Arts

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research (http://www.eda.kent.ac.uk/research/default.aspx) that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Course structure

The digital media group has interests in many areas of interactive multimedia and digital film and animation.

There is particular strength in web design and development, including e-commerce, e-learning, e-health; and the group has substantial experience in interaction design (eg, Usability and accessibility), social computing (eg, Social networking, computer mediated communication), mobile technology (eg, iPhone), virtual worlds (eg, Second Life) and video games. In the area of time-based media, the group has substantial interest in digital film capture and editing, and manipulation on to fully animated 3D modelling techniques as used in games and feature films.

Research Themes:
- E-Learning Technology (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=1)

- Medical Multimedia Applications and Telemedicine (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=2)

- Human Computer Interaction and Social Computing (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=3)

- Computer Animation and Digital Visual Effects (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=4)

- Mobile Application Design and Development (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=25)

- Digital Arts (http://www.eda.kent.ac.uk/research/theme_detail.aspx?gid=1&tid=26)

Research areas

- Intelligent Interactions

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

Careers

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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Our MSc in Data Science and Analytics aims to provide you with a comprehensive set of skills needed to handle, collect, store and analyse large and complex sets of data. Read more
Our MSc in Data Science and Analytics aims to provide you with a comprehensive set of skills needed to handle, collect, store and analyse large and complex sets of data. You will be taught by subject experts from both the School of Mathematics and the School of Computer Science and Informatics, which will allow you to see the topic from different perspectives and provides access to a wide range of modules across both Schools.

Throughout the course you will develop data handling and extraction skills, programming skills, machine learning and informatics skills, and problem solving and modelling skills. You will undertake case studies and project work which will give you the opportunity to put your skills into practice and provides valuable experience of working in the field. The dissertation project, typically undertaken with an industrial partner, will allow you to work with complex data in a creative manner and a problem-solving environment, as well as to communicate your ideas and findings effectively.

This programme is available on a one year full-time basis or a three-year part-time basis.

Distinctive features:

• A three-stage degree with exit points at PG Certificate, PG Diploma and Master’s level, allowing you to go into as much depth as you like.

• Acquire transferable data science and analytics skills that are highly sought after in a broad range of sectors.

• Learn from experts across the Schools of Mathematics and Computer Science and Informatics, and related University research groups specialising in various applications of data science and analytics, for example the Data Innovation Research Institute, Social Data Science Lab, and Health Modelling Centre Cymru.

• Gain valuable work experience; we have some placement opportunities available with industrial partners in the UK and abroad.

Structure

There are three stages to this programme. During the first stage, you will study a number of core modules covering fundamental subjects such as statistics, pattern recognition, data mining and optimisation. You may choose to exit after this first stage, at which point you may be able to obtain a PG Certificate qualification.

The second stage consists of a range of optional modules where you can explore subjects of interest to you and relevant your potential career path, for example web and social computing, time series and forecasting, supply chain modelling and visual communication and information design. You may choose to exit after the second stage, at which point you may be able to obtain a PG Diploma qualification.

The third and final stage consists of a three-month dissertation project, which will typically involve working with a company on a real problem of importance. Following successful completion of all modules and the dissertation, you may be able to obtain a Master’s qualification.

As a full-time student, you will complete all modules and your dissertation project in year one.

Part-time students will typically only need to be in the University for lectures and workshops for the equivalent of one day per week over 24 weeks for years 1 and 2. The dissertation project is undertaken during year 3.

Core modules:

Pattern Recognition and Data Mining
Statistical Methods
Optimisation Methods
Dissertation

Optional modules:

Information Processing in Python
Computer Science Topic 1: Web and Social Computing
Web Application Development
Distributed and Cloud Computing
Informatics
Visual Communication and Information Design
Time Series and Forecasting
Supply Chain Modelling
Statistics and Operational Research in Government
Credit Risk Scoring

Teaching

The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.

Programming skills and the use of relevant software packages will be taught in our dedicated computer suites. We often invite industry experts to give presentations, which our students are welcome to attend.

We will allocate three supervisors to you for your dissertation project. Usually your supervisors will be two members of academic staff with an interest or specialism in your field of research and a sponsor supervisor from the organisation you will work with during your project. You should meet regularly with your supervisor throughout your project.

Support

All of our students are allocated a personal tutor when they enrol on the course. A personal tutor is there to support you during your studies, and can advise you on academic and personal matters that may be affecting you. You should have regular meetings with your personal tutor to ensure that you are fully supported.

You will have access to the Trevithick Library, which holds our collection of mathematical and computer science-related resources, as well as to the other Cardiff University Libraries.

We will provide you with a copy of the Student Handbook, which contains details of each School’s policies and procedures. We also support students through the University’s virtual learning environment, Learning Central, where you can ask questions in a forum or find course-related documents.

Cardiff University also offers a wide range of support services which are open to our students, such as the Graduate Centre, counselling and wellbeing, financial and careers advisors, the international office and the Student Union.

Feedback:

We offer written and oral feedback, depending on the coursework or assessment you have undertaken. You will usually receive your feedback from the module leader. If you have questions regarding your feedback, module leaders are usually happy to give advice and guidance on your progress. We aim to provide you with feedback in a timely manner after you have submitted an assessment.

Assessment

We will assess your progress throughout the course. These assessments may take the form of written exam papers, in-module assignments, and the project dissertation, where knowledge and technical competence will be appraised. We may also use group work, oral presentations and poster displays to test communication, critical thinking and problem solving skills.

Career prospects

Data is increasingly cheap and ubiquitous, and is being collected on a massive scale. There is a significant and growing demand for professionals who can work efficiently and effectively with handling such complex and sizeable data and to extract insights to help inform decision-making. The skills you gain during the programme will equip you for graduate roles in this field. This new MSc programme enhances the already well-established related postgraduate taught programmes that the School of Mathematics offers, and is expected to be as successful in the recruiting of our graduates. Previous postgraduates have gone on to work with a variety of companies and Government organisations including the Office for National Statistics, Lloyds Banking Group, Nationwide, British Airways, Network Rail, UK Government, The Financial Times, Virgin Media, Welsh Water and Admiral Insurance.

If you prefer to continue on a more academic career pathway, you may choose to continue your studies with a PhD.

Placement

You will undertake a three-month placement for your dissertation project, based with one of our industrial partners in the UK or abroad.

We employ a dedicated Knowledge Exchange Officer who will work with you to obtain a placement and support you throughout your project.

Past placements achieved by our students have been with companies such as Admiral, British Airways, Lloyds Banking Group, Welsh Water, Office for National Statistics, Sainsbury’s, Virgin Media, Transport for London, and Deloitte.

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The computer science program is designed for students who have an undergraduate degree (or minor) in computer science, as well as those who have a strong background in a field in which computers are applied, such as engineering, science, or business. Read more

Program overview

The computer science program is designed for students who have an undergraduate degree (or minor) in computer science, as well as those who have a strong background in a field in which computers are applied, such as engineering, science, or business.

The degree is offered on a full- or part-time basis. Courses are generally offered in the afternoons and evenings to accommodate part-time students. Full-time students take three or four courses per semester and may be able to complete the course work in three semesters. Full-time students who are required to take additional bridge courses may be able to complete the course work in four semesters. Part-time students take one or two courses per semester and may be able to complete the course work in four to five semesters. The time required to complete a master's project is one semester, but can vary according to the student and the scope of the topic. Two semesters is typical.

Plan of study

The program consists of 30 credit hours of course work, which includes either a thesis or a project. Students complete one core course, three courses in a cluster, four electives, and a thesis. For those choosing to complete a project in place of a thesis, students complete one additional elective.

Clusters

Students select three cluster courses from the following areas (see website for individual area information):
-Computer graphics and visualization
-Data management
-Distributed systems
-Intelligent systems
-Languages and tools
-Security
-Theory

Electives

Electives provide breadth of experience in computer science and applications areas. Students who wish to include courses from departments outside of computer science need prior approval from the graduate program director. Refer to the course descriptions in the departments of computer science, engineering, mathematical sciences, and imaging science for possible elective courses.

Master's thesis/project

Students may choose the thesis or project option as the capstone to the program. Students who choose the project option must register for the Project course (CSCI-788). Students participate in required in-class presentations that are critiqued. A summary project report and public presentation of the student's project (in poster form) occurs at the end of the semester.

Curriculum

Thesis/project options differ in course sequence, see the website for a particular option's modules and a particular cluster's modules.

Other admission requirements

-Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
-Submit scores from the Graduate Record Exam.
-Have a minimum grade point average of 3.0 (B), and complete a graduate application.
-International applicants, whose native language is not English, must submit scores from the Test of English as a Foreign Language. A minimum score of 570 (paper-based) or 88 (Internet-based) is required.
-Applicants must satisfy prerequisite requirements in mathematics (differential and integral calculus, probability and statistics, discrete mathematics, and computer science theory) and computing (experience with a modern high-level language [e.g., C++, Java], data structures, software design methodology, introductory computer architecture, operating systems, and programming language concepts).

Additional information

Bridge courses:
If an applicant lacks any prerequisites, bridge courses may be recommended to provide students with the required knowledge and skills needed for the program. If any bridge courses are indicated in a student's plan of study, the student may be admitted to the program on the condition that they successfully complete the recommended bridge courses with a grade of B (3.0) or better (courses with lower grades must be repeated). Generally, formal acceptance into the program is deferred until the applicant has made significant progress in this additional course work. Bridge program courses are not counted as part of the 30 credit hours required for the master's degree. During orientation, bridge exams are conducted. These exams are the equivalent to the finals of the bridge courses. Bridge courses will be waived if the exams are passed.

Faculty:
Faculty members in the department are actively engaged in research in the areas of artificial intelligence, computer networking, pattern recognition, computer vision, graphics, visualization, data management, theory, and distributed computing systems. There are many opportunities for graduate students to participate in these activities toward thesis or project work and independent study.

Facilities:
The computer science department provides extensive facilities that represent current technology, including:
-A graduate lab with more than 15 Mac’s and a graduate library.
-Specialized labs in graphics, computer vision, pattern recognition, security, database, and robotics.
-Six general purpose computing labs with more than 100 workstations running Linux, Windows, and OS X; plus campus-wide wireless access.

Maximum time limit:
University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.

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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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This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Read more

This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Drawing from our cutting-edge research, the programme’s content covers all areas of speech and language processing, from phonetics, speech synthesis and speech recognition to natural language generation and machine translation.

This flexible programme provides research or vocational training and can be either freestanding or lead to PhD study. The modular nature of the programme allows you to tailor it to your own interests.

Taught by leading researchers from Linguistics & English Language, the Centre for Speech Technology Research and the School of Informatics, this programme combines elements of linguistics, computer science, engineering and psychology.

You will develop up-to-date knowledge of a broad range of areas in speech and language processing and gain the technical expertise and hands-on skills required to carry out research and development in this challenging interdisciplinary area.

Programme structure

You study two semesters of taught courses, followed by a dissertation.

Most core compulsory courses have both computational and mathematical content. A few optional courses need a stronger mathematical background. Courses in the second semester can be tailored to your own interests and abilities.

Compulsory courses:

  • Advanced Natural Language Processing
  • Computer Programming for Speech and Language Processing
  • Introduction to Phonology and Phonetics
  • Speech Processing

Option courses may include:

  • Advanced Topics in Phonetics: Speech Production and Perception
  • Automatic Speech Recognition
  • Introduction to Statistics and Experimental Design
  • Machine Learning and Pattern Recognition
  • Machine Translation
  • Natural Language Generation
  • Natural Language Understanding
  • Prosody
  • Simulating Language
  • Speech Synthesis
  • Univariate Statistics and Methodology using R

Learning outcomes

This programme aims to equip you with the technical knowledge and practical skills required to carry out research and development in the challenging interdisciplinary arena of speech and language technology.

You will learn about state-of-the-art techniques in speech synthesis, speech recognition, natural language processing, dialogue, language generation and machine translation.

You will also learn the theory behind such technologies and gain the practical experience of working with and developing real systems based on these technologies. This programme is ideal preparation for a PhD or working in industry.

Career opportunities

This programme will provide you with the specialised skills you need to perform research or develop technology in speech and language processing. It will also serve as a solid basis for doctoral study.



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The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. Read more

The theoretical application of mathematics to the world of finance allows you to make good, informed decisions in the face of uncertainty. With the growth and progression of business across the globe, the need for those who can understand quantitative financial methods are becoming increasingly lucrative, sought-after individuals. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting and expanding field.To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with our internationally respected Mathematics department, this comprehensive MSc programme will prepare you for careers in areas that require expert skills in mathematical and financial modelling, computational analysis and business management.

You will gain essential, complementary skills in multiple areas of study such as probability and stochastic analysis, option pricing, risk analysis and extremes, computational methods using MATLAB/C++, financial management and investment analysis. In addition, you will branch into a specialist area of study as you conduct a substantial project in a field of your choosing. The project will allow you to develop your research, computational and modelling skills with support from staff who have extensive experience working in multiple financial services and insurance industries.

Careers

The programme prepares you for a career in financial modelling within financial institutions themselves and within other sectors. It builds upon the success of Exeter’s well-established range of Masters programmes in Finance and related areas, many of whose graduates now hold senior positions in areas such as corporate financial strategy, financial planning, treasury and risk management and international portfolio management.

With the strong links between the College and the Met Office, the course also prepares you for career opportunities within reinsurance and credit risk management, especially in the development of financial models that rely on weather/climate systems.

Programme structure

The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.

Compulsory modules

Recent examples of compulsory modules are as follows; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Option Pricing; Fundamentals of Financial Management; Research Methodology; Advanced Mathematics Project.

Optional modules

Some recent examples are as follows; Topics in Financial Economics; Investment Analysis 1; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Investment Analysis II; Financial Modelling; Advanced Corporate Finance; Alternative Investments; Quantitative and Research Techniques; Advanced Econometrics; Dynamical Systems and Chaos; Pattern Recognition; Introduction to C++; Level 3 Mathematics Modules.



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Machine learning, data mining and high-performance computing are concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Read more
Machine learning, data mining and high-performance computing are concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Using state-of-the-art artificial intelligence methods, this technology builds computer systems capable of learning from past experience, allowing them to adapt to new tasks, predict future developments, and provide intelligent decision support. Bristol's recent investment in the BlueCrystal supercomputer - and our Exabyte University research theme - show our commitment to research at the cutting edge in this area.

This programme is aimed at giving you a solid grounding in machine learning, data mining and high-performance computing technology, and will equip you with the skills necessary to construct and apply these tools and techniques to the solution of complex scientific and business problems.

Programme structure

Your course will cover the following core subjects:
-Introduction to Machine Learning
-Research Skills
-Statistical Pattern Recognition
-Uncertainty Modelling for Intelligent Systems

Depending on previous experience or preference, you are then able to take optional units which typically include:
-Artificial Intelligence with Logic Programming
-Bio-inspired Artificial Intelligence
-Cloud Computing
-Computational Bioinformatics
-Computational Genomics and Bioinformatics Algorithms
-Computational Neuroscience
-High Performance Computing
-Image Processing and Computer Vision
-Robotics Systems
-Server Software
-Web Technologies

You must then complete a project that involves researching, planning and implementing a major piece of work. The project must contain a significant scientific or technical component and will usually involve a software development component. It is usually submitted in September.

This programme is updated on an ongoing basis to keep it at the forefront of the discipline. Please refer to the University's programme catalogue for the latest information on the most up-to-date programme structure.

Careers

Skilled professionals and researchers who are able to apply these technologies to current problems are in high demand in today's job market.

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The Intelligent Systems MSc degree course is designed to give graduates the understanding, practical knowledge and expertise to evaluate, design and build intelligent systems using an extensive range of tools and techniques. Read more

The Intelligent Systems MSc degree course is designed to give graduates the understanding, practical knowledge and expertise to evaluate, design and build intelligent systems using an extensive range of tools and techniques.

Key benefits

  • Located in central London, giving access to major libraries and leading scientific societies including the Chartered Institute for IT (BCS), the Institution of Engineering and Technology and the Institution of Mechanical Engineers (IMechE).
  • Opportunities to focus on topics such as intelligent systems, robotics and management skills while studying theoretical and practical electronic engineering and management topics.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in electronic engineering and related fields.

Description

The Intelligent Systems MSc will prepare you for work developing intelligent control and engineering systems. You will study Artificial Intelligence, Agents and Multi-agent Systems, Pattern Recognition, Computer Vision and Biologically Inspired Methods. There are also opportunities to explore a broad range of optional modules allowing you the freedom to develop your study pathway to reflect your interests.

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 an individual project of 15,000 words. 

Course purpose

For graduates in engineering, computing or a related scientific discipline, with a good knowledge of computer programming and mathematics, from this programme you will gain specialist training in designing, building and evaluating intelligent systems using a range of tools and techniques in 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.

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 gone on to pursue successful careers in industry, commerce and academia.



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Data mining, pattern recognition and machine learning are just three of the many applications that we take for granted and that are based on artificial intelligence software. Read more
Data mining, pattern recognition and machine learning are just three of the many applications that we take for granted and that are based on artificial intelligence software. Both the MSc and PG Diploma aim to equip students with the knowledge and skills necessary to make a valuable contribution to this rapidly evolving and widespread field of software development.

Full-time students take 4 courses each semester and must normally take courses marked with **

Semester 1
3D Modelling and Animation
Artificial Intelligence and Intelligent Agents
Data Mining and Machine Learning **
Rigorous Methods for Software Engineering
Robotics and Automation
Software Engineering Foundations

Semester 2
Advanced Interactive Design
Biologically Inspired Computation**
Computer Games Programming **
Research Methods and Project Planning**
Virtual Environments

After semester 2, students continue full-time on the MSc project

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Quantitative financial methods are one of the fastest growing areas of the present day banking and corporate environments. Read more
Quantitative financial methods are one of the fastest growing areas of the present day banking and corporate environments. The solution by Black, Scholes and Merton of the option pricing problem set off a revolution in finance resulting in the introduction of sophisticated mathematical techniques in the financial markets and corporate planning.

To understand, apply and develop these sophisticated methods requires a good understanding of both advanced mathematics and advanced financial theory. By combining the financial expertise in the University of Exeter Business School with expertise in the Mathematical Research Institute of the Mathematics Department at the University, this intensive MSc programme, available over 9 or 12 months, will prepare you for careers in areas such as international banking or international business. For those with a strong mathematical background, and a wish to pursue a finance career, this programme is the ideal introduction to this exciting field.

Programme structure

The taught element of the programme takes place between October and May and is arranged into two 12-week teaching semesters.

Compulsory modules

The compulsory modules can include; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Option Pricing; Fundamentals of Financial Management; Research Methodology and Advanced Mathematics Project;

Optional modules

Some examples of the optional modules are as follows; Topics in Financial Economics; Investment Analysis; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Investment Analysis; Financial Modelling; Advanced Corporate Finance; Alternative Investments; Quantitative and Research Techniques; Advanced Econometrics; Dynamical Systems and Chaos; Pattern Recognition; Introduction to C++ and Level 3 Mathematics Modules.

The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.

Learning and teaching

Teaching is by lectures, example classes, computer classes, tutorials, set work, project work, reading and self-study. The exact form and number of the lectures and tutorials varies from module to module and is chosen according to the material to be covered.
You will use the computer programming language Matlab and online financial databases such as Bloomberg and Datastream.

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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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