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Masters Degrees (Intelligent Systems)

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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.



Read less
Robotics requires a well-developed knowledge of areas ranging from computer science and artificial intelligence, to engineering and neuroscience, in order to produce hardware which can sense and manipulate the real world. Read more
Robotics requires a well-developed knowledge of areas ranging from computer science and artificial intelligence, to engineering and neuroscience, in order to produce hardware which can sense and manipulate the real world. This field has allowed us to develop everything from satellites and submarines, to racecars and robots.

Research carried out by our team has resulted in appearance in the Robot Soccer World Cup final, an autonomous robot fish in the London Aquarium, and a self-programming computer vision system.

Our course provides a comprehensive coverage of contemporary intelligent systems, with robots serving as a major example of the technology. Thanks to the leading research being undertaken in our School, you will gain a solid understanding of the foundations of this technology, exploring areas including:
-The principles by which sensed data are converted into useful information
-The practical aspects of developing intelligent and robotic systems
-Biologically-inspired robots
-Biometrics
-Computational intelligence

Our MSc Intelligent Systems and Robotics is delivered by our team of internationally recognised researchers, with expertise spanning the entire range of intelligent systems and experience of developing robots intended for land, under water and in the air.

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

This course is also available on a part-time basis.

Professional accreditation

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

Our expert staff

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

Our impressive external research funding stands at over £4 million and we participate in a number of EU initiatives and undertake projects under contract to many outside bodies, including government and industrial organisations.

In recent years we have attracted many highly active research staff and we are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist facilities

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

Your future

Our recent graduates have progressed to a variety of senior positions in industry and academia. Some of the companies and organisations where our former graduates are now employed include:
-Electronic Data Systems
-Pfizer Pharmaceuticals
-Bank of Mexico
-Visa International
-Hyperknowledge (Cambridge)
-Hellenic Air Force
-ICSS (Beijing)
-United Microelectronic Corporation (Taiwan)

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

Example structure

-MSc Project and Dissertation
-Computer Vision
-Group Project
-Intelligent Systems and Robotics
-Machine Learning and Data Mining
-Professional Practice and Research Methodology
-Programming Embedded Systems
-Artificial Neural Networks (optional)
-Constraint Satisfaction for Decision Making (optional)
-Creating and Growing a New Business Venture (optional)
-Digital Signal Processing (optional)
-Electronic System Design & Integration (optional)
-Evolutionary Computation and Genetic Programming (optional)
-High Level Logic Design (optional)
-Game Artificial Intelligence (optional)
-Virtual Worlds (optional)
-Natural Language Engineering

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From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. Read more

From software agents used in networking systems to embedded systems in unmanned vehicles, intelligent systems are being adopted more and more often. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of topics in computer science.

Core modules will give you a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like bio-inspired computing or text analytics, or broaden your approach with topics like mobile app development.

You’ll gain a broad perspective on intelligent systems, covering evolutionary models, statistical and symbolic machine learning algorithms, qualitative reasoning, image processing, language understanding and bio-computation as well as essential principles and practices in the design, implementation and usability of intelligent systems.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.




Read less
Robotics requires a well-developed knowledge of areas ranging from computer science and artificial intelligence, to engineering and neuroscience, in order to produce hardware which can sense and manipulate the real world. Read more
Robotics requires a well-developed knowledge of areas ranging from computer science and artificial intelligence, to engineering and neuroscience, in order to produce hardware which can sense and manipulate the real world. This field has allowed us to develop everything from satellites and submarines, to racecars and robots.

Research carried out by our team has resulted in appearance in the Robot Soccer World Cup final, an autonomous robot fish in the London Aquarium, and a self-programming computer vision system.

Our course provides a comprehensive coverage of contemporary intelligent systems, with robots serving as a major example of the technology. Thanks to the leading research being undertaken in our School, you will gain a solid understanding of the foundations of this technology, exploring areas including:

- The principles by which sensed data are converted into useful information
- The practical aspects of developing intelligent and robotic systems
- Biologically-inspired robots
- Biometrics
- Computational intelligence

Our MSc Intelligent Systems and Robotics is delivered by our team of internationally recognised researchers, with expertise spanning the entire range of intelligent systems and experience of developing robots intended for land, under water and in the air.

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

Read less
About the course. Read more

About the course

Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.

Computational Intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.

Modules include work based on research by the Centre of Computational Intelligence. With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems. Past students have published papers with their CCI project supervisors and gone on to PhD study.

Reasons to Study

• Internationally recognised reputation

our internationally recognised Centre of Computational Intelligence (CCI) inputs into the course allowing you to understand the current research issues related to artificial intelligence

• Benefit from our Research Expertise

modules include work-based on research by our Centre for Computational Intelligence (CCI) and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics; providing theoretically sound solutions to real-world decision making and prediction problems

• Flexible study options

full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work

• Dedicated robotics laboratory

have access to our Advanced Mobile Robotics and Intelligent Agents Laboratory. The laboratory contains a variety of mobile robots ranging from the Lego Mindstorms and Pioneers to the Wheelbarrow robot for bomb disposal

• Employment Prospects

artificial Intelligence is a growing industry worldwide, employment opportunities exist in areas such as games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering

Course Structure

Modules

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

We offer a great opportunity to boost your career prospects through an optional one year placement as part of your postgraduate studies. We have a dedicated Placement Unit which will help you obtain this. Once on your placement you will be supported by your Visiting Tutor to ensure that you gain maximum benefit from the experience. Placements begin after the taught component of the course has been completed - usually around June - and last for one year. When you return from your work placement you will begin your project.

Teaching and Assessment

The course consists of an induction unit, eight modules and an individual project. The summer period is devoted to work on the project for full-time students. If you choose to study via distance learning, you would normally take either one module per semester for four years or two modules per semester for four years plus a further year for the project.

Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.

Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.

Contact and learning hours

On-site students will have the lessons delivered by the module tutors in slots of three hours. In the full-time route, you can expect to have around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of independent study. There are also three non-teaching weeks when fulltime students can expect to spend around 40 hours on independent study each week.

To find out more

To learn more about this course and DMU, visit our website:

Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

Applying for a postgraduate course:

http://www.dmu.ac.uk/study/postgraduate-study/entry-criteria-and-how-to-apply/entry-criteria-and-how-to-apply.aspx

Funding for postgraduate students

http://www.dmu.ac.uk/study/postgraduate-study/postgraduate-funding-2017-18/postgraduate-funding-2017-18.aspx



Read less
About the course. Read more

About the course

Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.

Computational Intelligence encompasses the techniques and methods used to tackle problems not well solved by traditional approaches to computing. The four areas of fuzzy logic, neural networks, evolutionary computing and knowledge based systems encompass much of what is considered to be computational (or artificial) intelligence. There are opportunities to use these techniques in many application areas such as robot control and games development depending on your interests.

Modules include work based on research by the Centre of Computational Intelligence. With an established international reputation, their work focuses on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics, providing theoretically sound solutions to real-world decision making and prediction problems. Past students have published papers with their CCI project supervisors and gone on to PhD study.

Reasons to Study

• Internationally recognised reputation

our internationally recognised Centre of Computational Intelligence (CCI) inputs into the course allowing you to understand the current research issues related to artificial intelligence

• Benefit from our Research Expertise

modules include work-based on research by our Centre for Computational Intelligence (CCI) and focus on the use of fuzzy logic, artificial neural networks, evolutionary computing, mobile robotics and biomedical informatics; providing theoretically sound solutions to real-world decision making and prediction problems

• Flexible study options

full-time, part time or distance learning study options available; making the course suitable for recent graduates and professionals in work

• Dedicated robotics laboratory

have access to our Advanced Mobile Robotics and Intelligent Agents Laboratory. The laboratory contains a variety of mobile robots ranging from the Lego Mindstorms and Pioneers to the Wheelbarrow robot for bomb disposal

• Employment Prospects

artificial Intelligence is a growing industry worldwide, employment opportunities exist in areas such as games development, control systems, software engineering, internet businesses, financial services, mobile communications, programming, and software engineering

Course Structure

Modules

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

We offer a great opportunity to boost your career prospects through an optional one year placement as part of your postgraduate studies. We have a dedicated Placement Unit which will help you obtain this. Once on your placement you will be supported by your Visiting Tutor to ensure that you gain maximum benefit from the experience. Placements begin after the taught component of the course has been completed - usually around June - and last for one year. When you return from your work placement you will begin your project.

Teaching and Assessment

The course consists of an induction unit, eight modules and an individual project. The summer period is devoted to work on the project for full-time students. If you choose to study via distance learning, you would normally take either one module per semester for four years or two modules per semester for four years plus a further year for the project.

Teaching is normally delivered through lectures, seminars, tutorials, workshops, discussions and e-learning packages. Assessment is via coursework only and will usually involve a combination of individual and group work, presentations, essays, reports and projects.

Distance learning material is delivered primarily through our virtual learning environment. Books, DVDs and other learning materials will be sent to you. We aim to replicate the on-site experience as fully as possible by using electronic discussion groups, encouraging contact with tutors through a variety of mediums.

Contact and learning hours

On-site students will have the lessons delivered by the module tutors in slots of three hours. In the full-time route, you can expect to have around 12 hours of timetabled taught sessions each week, with approximately 28 additional hours of independent study. There are also three non-teaching weeks when fulltime students can expect to spend around 40 hours on independent study each week.

Academic expertise

Taught by experienced research staff from the Centre for Computational Intelligence (CCI), an internationally recognised centre highly rated in the most recent Government Research Assessment Exercise, you will gain a professional qualification that gives substantially enhanced career and research prospects in both traditional computing areas and in the expanding area of computational intelligence.

To find out more

To learn more about this course and DMU, visit our website:

Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

Applying for a postgraduate course:

http://www.dmu.ac.uk/study/postgraduate-study/entry-criteria-and-how-to-apply/entry-criteria-and-how-to-apply.aspx

Funding for postgraduate students

http://www.dmu.ac.uk/study/postgraduate-study/postgraduate-funding-2017-18/postgraduate-funding-2017-18.aspx



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This international Master’s programme gives insights into cutting edge resarch in robotics and artificial intelligence. The programme is centred around a "raise your robot" theme. You get access to a robot platform from day one, which you will give more and more advanced capabilities as the courses are progressing. Read more

This international Master’s programme gives insights into cutting edge resarch in robotics and artificial intelligence. The programme is centred around a "raise your robot" theme. You get access to a robot platform from day one, which you will give more and more advanced capabilities as the courses are progressing.

The programme is offered by the nationally and internationally renowned Centre for Applied Autonomous Sensor Systems (AASS) at Örebro University. As a student, you will be immersed in one of Sweden's largest academic research centres in robotics and intelligent systems. The outcomes of our ongoing international research projects feed into all of the courses. Vice versa, student projects and thesis works typically contribute to our research projects with industry partners.



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Why this course?. This MSc focuses on state-of-the-art technologies for autonomous control and machine learning with applications in robotics, sensor networks, big data analytics, and autonomous agents. Read more

Why this course?

This MSc focuses on state-of-the-art technologies for autonomous control and machine learning with applications in robotics, sensor networks, big data analytics, and autonomous agents.

Emphasis is given to topics that support a new emerging generation of self-sustaining and intelligent devices created for the Internet of Things, Ubiquitous Computing, and Industry 4.0 environments.

This degree is designed to provide a wide-ranging background in autonomous technologies that can be applied in a variety of disciplines. 

In addition to traditional technologies related to robotics, embedded systems, design, and control, students will be exposed to system-level design methods and state-of-the-art theory behind some of the newest and most promising fields of artificial intelligence.

Applications include autonomous mobile systems, digital manufacturing, Big Data analytics, Internet of things device engineering, and artificial intelligence programming.

The MSc is delivered jointly by the Departments of Electronic & Electrical Engineering, and Design, Manufacture & Engineering Management.

This ensures you have access to academic leaders in the fields of machine learning, autonomous systems, digital manufacturing and design engineering.

You’ll study

You’ll take two semesters of compulsory and optional taught classes. These are followed by a three-month research project in your chosen area. Opportunities exist to do the project through the departments' competitive MSc industrial internships.

The internships are offered in collaboration with selected department industry partners. You’ll address real-world engineering challenges facing the partner, with site visits, access and provision of relevant technical data and/or facilities provided, along with an industry mentor and academic supervisor.

Facilities

We’ve a wide range of excellent teaching spaces including interactive flexible learning spaces, and state-of-the-art facilities. Our Technology and Innovation Centre (TIC) is home to a number of world class labs where students will have an opportunity to undertake research projects in relevant areas. The University is also home to some key and relevant industry engagement research centres, including:

Industry engagement

Interaction with industry is provided through our internships, teaching seminars and networking events. The departments deliver monthly seminars to support students’ learning and career development.

Xilinx, Texas Instruments, MathWorks, and Leonardo are just a few examples of the industry partners you can engage with during your programme of study.

Learning & teaching

We use a blend of teaching and learning methods including interactive lectures, problem-solving tutorials and practical project-based laboratories.

Our technical and experimental officers are available to support and guide you on individual subject material. Each module comprises approximately five hours of direct teaching per week.

To enhance your understanding of the technical and theoretical topics covered in these, you're expected to undertake a further five to six hours of self-study, using our web-based virtual learning environment (MyPlace), research journals and library facilities.

The teaching and learning methods used ensure you'll develop not only technical engineering expertise but also communications, project management and leadership skills.

Assessment

A variety of assessment techniques are used throughout the course. Each module has a combination of written assignments, individual and group reports, oral presentations, practical lab work and, where appropriate, an end-of-term exam.

Assessment of the summer research project consists of four elements, with individual criteria:

  1. Interim report (10%, 1,500 to 3,000 words) – The purpose of this report is to provide a mechanism for supervisors to provide valuable feedback on the project’s objectives and direction.
  2. Poster Presentation (15%) – A vital skill of an engineer is the ability to describe their work to others and respond to requests for information. The poster presentation is designed to give you an opportunity to practise that.
  3. Final report (55%) – This assesses the communication of project objectives and context, accuracy and relevant of background material, description of practical work and results, depth and soundness of discussion and conclusions, level of engineering achievement and the quality of the report’s presentation.
  4. Conduct (20%) - Independent study, project and time management are key features of university learning. The level of your initiative & independent thinking and technical understanding are assessed through project meetings with your supervisor and your written logbooks.

Careers

Job titles include:

  • Graduate controls engineer
  • Graduate software engineer
  • Lecturer
  • Roboticist
  • Data analytics programmer

Employers include:

  • Xilinx
  • Texas Instruments
  • MathWorks
  • Leonardo
  • Siemens
  • Jaguar/Land Rover


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The MSc Machine Intelligence aims to equip students and engineering professionals through a diverse range of research informed learning, with the skills to maintain a future-thinking career. Read more

The MSc Machine Intelligence aims to equip students and engineering professionals through a diverse range of research informed learning, with the skills to maintain a future-thinking career. The programme goes beyond current technology, looking at predicting future innovation by equipping learners with the tools to see through media hype and effectively analyse the evolution of future technologies and engage with these technologies as they emerge.

Whether you're looking to deepen and diversify your industrial experience or continue your education through an innovative Master's degree, this programme provides an ideal opportunity to develop your technical and intellectual skills, staying one step ahead. 

The programme provides the opportunity to explore: future technologies; robotics; cybernetics and intelligent systems; distributed systems; advanced design and ergonomics; securing future technologies; and future business thinking, all set within a forward-thinking context. This programme offers the opportunity to participate in a highly motivated intellectual environment with research-active tutors and like-minded peers, whilst exploring and engaging with cutting-edge future technologies.

Outcomes

The aims of the programme are to:

  • Show you how to analyse, design, implement and manage intelligent and future focused technologies and systems in the context of engineering-related issues facing global societies
  • Provide you with the skills to further your career in these areas
  • Support you in understanding the innovative and pioneering approaches in this field and to be able to apply them to the solution of present, near future and future real-world problems in developing novel industrial and commercially-relevant solutions.

Course content

  • Future Technologies
  • Robotics
  • Cybernetics and Intelligent Systems
  • Distributed Systems
  • Research, Planning and Communication
  • Future Business Thinking
  • Securing Future Technologies
  • Individual Research Project.

Assessment

Assessments include examinations, coursework, group work and an individual project.

Careers

Postgraduate students from this programme will find employment opportunities as futurologists, engineers, scientists and technical managers in the private sector (engineering design firms, engineering consultancy, communications companies, social media companies and similar), in the public sector (local government, town and country planning), an entrepreneur or they may wish to pursue further qualifications such as a PhD within the Faculty of Engineering and Science at the University of Greenwich to become even more specialised. City banks, currency and stocks trading companies, consultancies, government agencies and NGOs will also be interested in employing the type of future orientated intelligent systems engineers that will graduate from this MSc.

Specialised equipment

Online resources: Students will require access to existing online resources such as Moodle, e-mails, library online resources, databases, Web of Knowledge, Scopus, Internet of Things, Internet of Everything.

Hardware: Computers, laboratory equipment to include but not limited to: experimental and laboratory equipment to support practical based learning (hardware and software development systems, robotic hardware, mobile robots, cybernetics hardware and software, Internet of Things, Sensors and Systems, WiFi development, 3D printers, laser cutters, 3D scanners, cutting edge single board computers)

Software: Matlab, Simulink, C/C++ compilers, development systems, networking and communication protocol monitoring and development.

Robotics: A specialist robotics laboratory has been developed containing a Robothespian industrial robotic arm, mobile robots and other robotic actuators and systems.



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Artificial intelligence deals with the theory, design, application, and development of biologically, socially and linguistically motivated computational paradigms. Read more
Artificial intelligence deals with the theory, design, application, and development of biologically, socially and linguistically motivated computational paradigms.

You focus on linking artificial intelligence techniques to real-world applications and projects, including artificial intelligence in business and financial applications, artificial intelligence in games, artificial intelligence in biological sciences and medicine, and artificial intelligence in industrial control.

Our unique course covers the theoretical, applied and practical aspects of artificial intelligence, with an emphasis on:
-Genetic algorithms
-Evolutionary programming
-Fuzzy systems
-Neural networks
-Connectionist systems
-Hybrid intelligent systems

Our School is a community of scholars leading the way in technological research and development. Today’s computer scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world’s top scientists, and our work is driven by creativity and imagination as well as technical excellence.

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

This course is also available on a part-time basis.

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

Our expert staff

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

Our impressive external research funding stands at over £4 million and we participate in a number of EU initiatives and undertake projects under contract to many outside bodies, including government and industrial organisations.

In recent years we have attracted many highly active research staff and we are conducting world-leading research in areas such as evolutionary computation, brain-computer interfacing, intelligent inhabited environments and financial forecasting.

Specialist facilities

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

Your future

Our course opens up employment opportunities designing intelligent software – in banks and businesses designing prediction systems, in computer games companies designing adaptive games, in pharmaceutical companies designing intelligent systems that model a given drug and its various interactions, and in heavy industries designing control systems.

Our recent graduates have progressed to a variety of senior positions in industry and academia. Some of the companies and organisations where our former graduates are now employed include:
-Electronic Data Systems
-Pfizer Pharmaceuticals
-Bank of Mexico
-Visa International
-Hyperknowledge (Cambridge)
-Hellenic Air Force
-ICSS (Beijing)
-United Microelectronic Corporation (Taiwan)

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

Example structure

Postgraduate study is the chance to take your education to the next level. The combination of compulsory and optional modules means our courses help you develop extensive knowledge in your chosen discipline, whilst providing plenty of freedom to pursue your own interests. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore to ensure your course is as relevant and up-to-date as possible your core module structure may be subject to change.

Artificial Intelligence - MSc
-MSc Project and Dissertation
-Machine Learning and Data Mining
-Professional Practice and Research Methodology
-Group Project
-Intelligent Systems and Robotics
-Computer Vision (optional)
-Game Artificial Intelligence (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Natural Language Engineering (optional)
-Artificial Neural Networks (optional)
-Virtual Worlds (optional)
-Creating and Growing a New Business Venture (optional)
-Learning and Computational Intelligence in Economics and Finance (optional)

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The Department of Computer Science at Aberystwyth has a strong research focus on techniques and applications of intelligent systems, working with many major companies. Read more

About the course

The Department of Computer Science at Aberystwyth has a strong research focus on techniques and applications of intelligent systems, working with many major companies. Our taught Masters degrees draw on this focus, and link to the expertise and interests of the Department. They are designed to meet the needs of both students wanting a foundation for a career in research, and those wanting to expand on their skills to accelerate their industrial career.

Contemporary software is frequently developed to function in distributed systems. Applications are deployed across multiple computers, interacting to provide services and to solve problems in a distributed way. This Masters course is suitable for students intending to pursue a career in the software industry, and is a qualifying Masters Degree for Chartered Engineer status. It can also lead to a career in research.

The course in Software Engineering is a two year full-time programme. This degree is the same as the one year MSc in Computer Science (Software Engineering) - G493, with the addition that the student spends a year working in industry after the taught part of the course.

Year one of the course is divided into two parts over three semesters. In part one, you will establish a breadth of necessary skills in a number of core modules whilst directing your own study by choosing specialist modules, worth a total of 120 credits. In part two, you will apply your learning in the individual dissertation worth an additional 60 credits.

Previous study topics have included: Transmission of MIDI music over internet connection, Designing a network intrusion detection system, Online results and statistics using web service technology, Supply chain management system applications and Prototype railway track measurement system.

Whatever your own previous experience or future aspiration, with this course you will benefit from the marvellous integration of cutting-edge theory and practical application, within a world-class department. The most recent Research Excellence Framework (2014) assessment found that 100% of the impact research the department of Computer Science undertakes is world leading.

Course content

Year 1

Core modules:

Advanced Software Engineering
Machine Learning for Intelligent Systems
Mobile Solutions

Optional modules:

Enterprise Systems Development
Fundamentals of Intelligent Systems
Internet Technologies
Research Skills and Personal Development for Scientists
Statistical Concepts, Methods and Tools
The Object Oriented Programming Paradigm
Research Skills and Personal Development for Scientists (1520)

Year 2

Core modules:

MSC Project
Sandwich Year (PG)

Optional modules:

Statistical Concepts, Methods and Tools

Contact time

Approximately 12 hours a week in the first two semesters. During semester three you will arrange your level of contact time with your assigned supervisor.

Assessment

The taught part of the course is delivered and assessed through lectures, student seminars, practical exercises, case studies, course work and formal examinations. The subsequent successful submission of your research dissertation leads to the award of an MSc.

Industrial Year

This degree is the same as the one year MSc in Computer Science (Software Engineering), with the addition that the student spends a year working in industry after the taught part of the course.

• Students study at Aberystwyth University from September to May, and are supported in applying for suitable jobs in the software
industry.
• They work in the UK from June to the following May.
• They return to Aberystwyth to complete their dissertation from June to September

The work in industry is paid employment, not just work experience. Typical annual salaries for an industrial year are between £11,000 and £15,000.

Students wishing to do the industrial year are assisted in finding a place in industry. There is assistance with preparing an appropriate CV, training in what to expect at an interview, and practice in being interviewed by experienced industry interviewers. The Department of Computer Science sends about 70 students each year for a year's experience in industry, and has many contacts in companies enthusiastic to take good students from Aberystwyth University.

As these are paid jobs for companies, we cannot guarantee any student a job - the companies select the employees they want. Students that are unable to find a job can complete the Masters degree without an industrial year.

There is an additional but much reduced fee for the year in industry (presently £800 for the year), and members of staff stay in touch electronically and by visiting students during the year.

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The MSc Advanced Computer Science course prepares students to work in roles that require the use of data management, analysis and presentation tools, the development of software to deliver services or to control complex processes and equipment, or to provide system analysis and development consultancy to a varied range of clients. Read more

Overview

The MSc Advanced Computer Science course prepares students to work in roles that require the use of data management, analysis and presentation tools, the development of software to deliver services or to control complex processes and equipment, or to provide system analysis and development consultancy to a varied range of clients. The course does not require background in programming or data analysis and for those with no such background appropriate training is offered to catch up with others who already have such training or experience. The course aims to match the needs of business that compete globally in a world driven by advances in information technology. The programme aims to develop both technical and people skills making our graduates ready for jobs that offer high satisfaction and regular challenge at the same time. The first semester of the course is organised into modules delivered intensively over three week periods. The second semester is organised using usual semester-long modules with the difference that all these modules are assessed by coursework only. The summer semester is dedicated to a Master’s level research or development project

See the website https://www.keele.ac.uk/pgtcourses/advancedcomputersciencemsc/

Course Aims

The aims of the programme are to equip students with knowledge of a range cutting-edge areas of computer science research and applications and to prepare students to be successful in a variety of computer science related jobs. The course covers advanced computer science topics, including user interaction design, big data, cloud computing, security, intelligent systems and mobile-oriented web applications. The course also provides a good grounding in collaborative team work and general skills for technology consultants.

Core Modules:

User Interaction Design (15 credits – Semester 1): The module provides the knowledge and skills required for a student to be able to work on User Interaction Design based on an evaluated assessment of the factors associated with a given application or user interaction scenario.

Distributed Intelligent Systems (15 credits – Semester 1): This module provides the knowledge and skills required for a student to be able to develop applications to control intelligent systems in a distributed and collaborative context, including the programming of robots or intelligent home appliances (e.g. TV, fridge, etc. equipped with embedded computers).

Statistical Techniques for Data Analytics (15 credits – Semester 1): This module provides the knowledge and skills required for a student to be able to develop applications to store, process, distribute, visualise and analyse large volumes of big data using distributed databases, statistical techniques and machine intelligence methods.

Cloud Computing (15 credits – Semester 2): The module provides the knowledge and skills required for a student to be able to understand the principles of operations of cloud computing and to develop applications for cloud computing environments, e.g. data storage and distribution, software-as-service, interactive content services.

Web Technologies and Security (15 credits – Semester 2): To module provided an understanding of contemporary web technologies used for both server and client side development of web applications, with particular focus on mobile applications, and an understanding of security aspects of such applications and of the defence methods and techniques employed to provide security.

Collaborative Application Development (15 credits – Semester 2): The module places students in a real world scenario requiring co-operation and communication as well as analysis and design skills. This will involve work for a real world client working as a development team.

Problem Solving Skills for Consultants (15 credits – Semester 1 & 2): This module explores skills such as project management, communication and team working and building. It also provides knowledge of ethical, legal and social issues related to the development and deployment of Information Technology.

Optional Modules:

System Design & Programming (15 credits – Semester 1): This module provides the knowledge and skills required for a student to be able to design software systems and write object oriented programs in an appropriate programming language (e.g. Java, C#).

Research Horizons (15 credits – Semester 1): To module provides the knowledge for a student about a selected computer science research area and the skills required for the development of a mini-project in this area

Project or Industrial Placement

MSc Project or Industrial Placement (60 credits – Semester 3): Provides an integration of concepts taught on the course in either an academic or business environment

Teaching & Assessment

All first semester 15 – credit taught modules, with the exception of one module delivered over two semesters, will be delivered in block mode, i.e. each of these modules will be delivered over a period of six consecutive weeks. In any week at most two block mode modules will be scheduled to be delivered during the first semester. All taught modules in the second semester are delivered along the whole semester.

The taught modules are mainly assessed by coursework, with examinations in some of the modules. Project assessment is based largely on a substantial final report.

Additional Costs

Additional costs may be incurred for text books, inter-library loans and potential overdue library fines. Some travel costs may be incurred if an external project or placement is undertaken; any such costs will be discussed with the student before the project is confirmed. It will be possible for the student to select an internal project and that would not incur any additional travel costs.

Find information on Scholarships here - http://www.keele.ac.uk/studentfunding/bursariesscholarships/

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The MSc in Intelligent Robotics will provide the opportunity to learn about the growing area of mobile and autonomous robotics, and intelligent systems. Read more
The MSc in Intelligent Robotics will provide the opportunity to learn about the growing area of mobile and autonomous robotics, and intelligent systems. You will gain experience in an exciting wide range of topics, providing you hands-on experience. You will learn about the development of embedded control systems for robots, intelligent algorithms and their application to robotics, communications and systems programming, all with a focus on the practical implementation, both in hardware and simulation. The MSc culminates in a large group project focussed on collective robotic systems, ranging from ground-based units to flying robots. You will have the opportunity to work in a state of the art, dedicated, robotics laboratory for some of your modules and your final project, see the York Robotics Laboratory website for more details on the lab.

The MSc is intended for students who want to learn about robotic and autonomous systems for employment in related industries, or who are seeking a route into a PhD.

The broad aims of the course are to provide:
-A thorough grounding in the use of scientific and engineering techniques as applied to intelligent robotic systems
-A detailed knowledge of the development and deployment of intelligent robotic systems
-A detailed knowledge of the latest developments in intelligent robotics and an ability to reflect critically on those developments
-A detailed understanding of engineering collective robotic systems with emergent behaviours
-Experience of undertaking a substantial group project, on a subject related to research in autonomous robotic systems

Group Project

The aim of this substantial group project is to immerse the students in a life-like scenario of a group of engineers developing a large scale collective robotic system. The project will involve the design, construction and implementation of the control of a heterogeneous collective robotic system, providing students with practical experience of project management and team skills. The system will include both software (such as individual and collective robotic control, low-level programming) and hardware (such as hardware design or customisation) components. The project will culminate in the design and realisation of a collective robotic system that will undergo various test scenarios in the robotics laboratory.

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

In the Summer term, the project will get under way. Groups of 4-6 students will be formed, assigned a target system to design, and provided with a budget. In this term, the students will prepare a design document that will be followed for the remainder of the project. Detailed system specifications will be established and initial prototypes developed. You will make full use of the Robotics Laboratory and spend the vast majority of your time working on robotic systems and attempting to develop an innovative solution to the problem given. Full technical support is available in the laboratory.

A final presentation of each group is done in September where live demos of the system developed have to be provided. This is combined with a group presentation on the work undertaken and contributions made by each individual. Group documentation is submitted along with an individual report.

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Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry. Read more

Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry.

Intelligent and autonomous systems are increasingly important in all areas of human life and activity from medicine and space exploration to agriculture and entertainment.

Understanding and developing autonomous systems involves a range of skills and knowledge including designing interactive systems with both human and machine elements, and modelling and building systems that can sense and learn.

Machine learning is at the heart of autonomous and intelligent systems, including computer vision and robotics. It also underpins the recent developments in data analytics across many fields.

You will learn to use new knowledge to solve complex machine learning and autonomous systems problems. You’ll develop a range of skills including the theory of machine learning, artificial intelligence, autonomous systems design and engineering, and the implications for humans of interacting more and more with intelligent and autonomous systems.

You will be taught by academics from the Department of Computer Science with expertise in machine learning, autonomous systems, artificial intelligence and human-computer interaction. This course has been designed in collaboration with the Department of Electronic and Electrical Engineering who offer expertise in robotics.

You will study in a research-led department with a supportive postgraduate community. You’ll learn in our bespoke computer laboratory and be exposed to the latest ideas and technology. The department has strong links to industry both nationally and internationally.

With machine learning and autonomous systems forming an essential part of a number of key industries, our MSc graduates will be highly sought after by employers.

You’ll gain the knowledge and transferable skills for a career in a wide range of industries, or for further study at PhD level. Graduates from the department have gone on to work in a wide variety of sectors, including IT consultancy, software development, banking and education.

Visit the website.



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This course runs in Germany. This course covers a range of essential topics related to distributed computing systems. Yet these modules are not isolated; each one takes its place in the field in relation to others. Read more

About the course

This course runs in Germany.

This course covers a range of essential topics related to distributed computing systems. Yet these modules are not isolated; each one takes its place in the field in relation to others.

The emphasis in the course is to build the connections between topics, enabling software engineers to achieve co-operation between distinct autonomous systems under constraints of cost and performance requirements.

The course is suitable for:

Recent graduates in Electrical or Electronic Engineering or Computer Science, who wish to develop their skills in the field of distributed computing systems.
Practicing engineers and computer professionals who wish to develop their knowledge in this area.
People with suitable mathematical, scientific or other engineering qualifications, usually with some relevant experience, who wish to enter this field.

Aims

The past few years have witnessed that Grid computing is evolving as a promising large-scale distributed computing infrastructure for scientists and engineers around the world to share various resources on the Internet including computers, software, data, instruments.

Many countries around the world have invested heavily on the development of the Grid computing infrastructure. Many IT companies have been actively involved in Grid development. Grid computing has been applied in a variety of areas such as particle physics, bio-informatics, finance, social science and manufacturing. The IT industry has seen the Grid computing infrastructure as the next generation of the Internet.

The aim of the programme is to equip high quality and ambitious graduates with the necessary advanced technical and professional skills for an enhanced career either in industry or leading edge research in the area of distributed computing systems.

Specifically, the main objectives of the programme are:

To critically appraise advanced technologies for developing distributed systems;
To practically examine the development of large scale distributed systems;
To critically investigate the problems and pitfalls of distributed systems in business, commerce, and industry.

Course Content

Compulsory Modules:

Computer Networks
Network Security and Encryption
Distributed Systems Architecture
Project and Personal Management
High Performance Computing and Big Data
Software Engineering
Embedded Systems Engineering
Intelligent Systems
Dissertation

Special Features

Electronic and Computer Engineering is one of the largest disciplines in the University, with a portfolio of research contracts totalling £7.5 million, and has strong links with industry.

The laboratories are well equipped with an excellent range of facilities to support the research work and courses. We have comprehensive computing resources in addition to those offered centrally by the University. The discipline is particularly fortunate in having extensive gifts of software and hardware to enable it to undertake far-reaching design projects.

We have a wide range of research groups, each with a complement of academics and research staff and students. The groups are:

Media Communications
Wireless Networks and Communications
Power Systems
Electronic Systems
Sensors and Instrumentation.

Women in Engineering and Computing Programme

Brunel’s Women in Engineering and Computing mentoring scheme provides our female students with invaluable help and support from their industry mentors.

Accreditation

Distributed Computing Systems Engineering is accredited by the Institution of Engineering and Technology (IET).

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