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Masters Degrees (Evolutionary Computing)

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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. 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

• Computational Intelligence Research Methods
• Artificial Intelligence (AI) Programming
• Mobile Robots
• Fuzzy Logic
• Artificial Neural Networks
• Evolutionary Computing
• Applied Computational Intelligence
• Intelligent Mobile Robots
• Individual Project

Optional placement
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

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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. 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

• Computational Intelligence Research Methods
• Artificial Intelligence (AI) Programming
• Mobile Robots
• Fuzzy Logic
• Artificial Neural Networks
• Evolutionary Computing
• Applied Computational Intelligence
• Data Mining
• Individual Project

Optional placement
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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Taught by expert researchers, this innovative MSc combines evolutionary anthropology, focusing on the behaviour of human and non-human primates, with evolutionary, developmental and cognitive psychology. Read more
Taught by expert researchers, this innovative MSc combines evolutionary anthropology, focusing on the behaviour of human and non-human primates, with evolutionary, developmental and cognitive psychology.

You gain an interdisciplinary understanding of the origins and functions of human behaviour and can select from a range of advanced topics such as evolutionary anthropology, primatology, human behaviour, cognitive psychology, developmental psychology and intergroup relationships.

The programme places a strong emphasis on critical thinking and understanding of both the broad fields and the specialisms within. Core to the programme is the development of research methods, culminating in a piece of original research, written up in the form of a publication-ready journal article. The MSc in Evolution and Human Behaviour is a perfect foundation for PhD research: it provides theoretical background, discipline specific knowledge and advanced, quantitative research methods.

Visit the website https://www.kent.ac.uk/courses/postgraduate/190/evolution-and-human-behaviour

Why study with us?

- A unique, interdisciplinary, combination of Evolutionary Anthropology and Psychology.

- Taught by expert, active researchers in evolutionary approaches to understanding behaviour.

- Select from a range of advanced topics such as Evolutionary Anthropology, Primatology, Human Behaviour, Developmental Psychology & Cognitive Neuroscience.

- Perfect foundation for future PhD research: theoretical background, discipline-specific knowledge and advanced research methods.

- For students with an undergraduate degree in anthropology, psychology, biology or a related discipline.

- A research component that results in a publication-ready journal article.

Course structure

The programme places a strong emphasis on critical thinking and understanding of both the broad field and the specialisms within. Core to the programme is the development of research methods, culminating in a piece of original research, written up in the form of a publication ready journal article.

Modules

Please note that modules are subject to change. Please contact the School for more detailed information on availability.

SE992 - Advanced Topics in Evolutionary Anthropology (15 credits)
SP801 - Statistics and Methodology (40 credits)
SE993 - Advanced Topics in Primate Behaviour (15 credits)
SE994 - Advanced Topics in HUman Behaviour (15 credits)
SP844 - Advanced Topics in Group Processes (20 credits)
SP851 - Advanced Topics in Cognitive Development (20 credits)
SP856 - Groups and Teams in Organisations (15 credits)
SP827 - Current Issues in Cognitive Psychology and Neuropsychology (40 credits)
SP842 - Advanced Developmental Social Psychology (20 credits)
SE855 - Research Project (Evolution & Human Behaviour) (60 credits)

Assessment

Assessment is by computing tests, unseen examinations, coursework and a project report.

Programme aims

This programme aims to:

- provide the opportunity for advanced study of human behaviour from an evolutionary perspective, combining approaches from both evolutionary anthropology and evolutionary psychology

- provide teaching that is informed by current research and scholarship and that requires you to engage with aspects of work at the frontiers of knowledge

- help you to develop research skills and transferable skills in preparation for entering academic or other careers as an evolutionary scientist

- enable you to manage your own learning and to carry out independent research

- help you develop general critical, analytic and problem-solving skills that can be applied in a wide range of settings.

Careers

As a School recognised for its excellence in research we are one of the partners in the South East Doctoral Training Centre, which is recognised by the Economic and Social Research Council (ESRC). This relationship ensures that successful completion of our courses is sufficient preparation for research in the various fields of social anthropology. Many of our students go on to do PhD research. Others use their Master’s qualification in employment ranging from research in government departments to teaching to consultancy work overseas.

Higher degrees in anthropology create opportunities in many employment sectors including academia, the civil service and non-governmental organisations through work in areas such as human rights, journalism, documentary film making, environmental conservation and international finance. An anthropology degree also develops interpersonal and intercultural skills, which make our graduates highly desirable in any profession that involves working with people from diverse backgrounds and cultures.

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

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Our flagship course blends theory and practice, giving you a strong grounding for a career in industry or research. This continually evolving course has been running for over 40 years and is well supported by the UK Engineering and Physical Sciences Research Council (EPSRC). Read more

About the course

Our flagship course blends theory and practice, giving you a strong grounding for a career in industry or research. This continually evolving course has been running for over 40 years and is well supported by the UK Engineering and Physical Sciences Research Council (EPSRC).

The core modules provide you with the basic skills you’ll need to become a control and systems engineer. You’ll take advanced modules in current areas of interest and complete a research-level dissertation project.

Push yourself further

We have cutting edge facilities and technology, including: advanced control
and systems software, modelling, simulation and controller design tools, robotics and a flexible manufacturing systems laboratory, evolutionary computing laboratory and clean facilities for the assembly of satellite instrumentation.

Make your mark

You could pursue a career with a large international organisation or government department. Our graduates work in sectors such as manufacturing, power generation and sustainable energy, with companies including British Airways, Jaguar Land Rover, NASA, IBM, Rolls-Royce and Unilever.

A masters from Sheffield is the mark of someone with the skills to apply their knowledge in industry, anywhere in the world. Our MSc in Advanced Control and Systems Engineering is accredited by the Engineering Council UK, IET and InstMC. These marks of assurance mean our degrees meet the high standards set by the engineering profession.

A Sheffield masters is a strong foundation for a career in industry or research.

Industry links

We have strong links with industrial partners such as Rolls-Royce and BAE Systems. Our industrial partners help us to design our courses, making sure you learn the right skills.

Rolls-Royce has a research and development centre here, using our expertise to explore today’s challenges. Our masters students often work side by side with researchers at these facilities.

A stimulating environment

The 2014 Research Excellence Framework (REF) rates us No 1 in the UK for research output, ahead of Oxford and Cambridge, and No 3 for overall research excellence. Our world-class reputation attracts highly motivated staff and students.

You’ll be taught by staff who work on real-world projects, developing new ideas – for submarines, robots, Formula One and even space exploration. Their approach to teaching is just as innovative: ideas like the award-winning take-home lab kit and e-puck mobile robotics activities help you develop the problem-solving skills you need for a trailblazing career.

Core modules

Foundations of Control Systems; State-Space, Optimal Control and Nonlinear Systems; Signal Processing and Estimation; Embedded Systems and Rapid Control Prototyping; Advanced Industrial Control; Control Systems Project and Dissertation.

Examples of optional modules

Intelligent and Vision Systems; Nonlinear and Hybrid Systems; Robotic and Autonomous Systems; Multisensor and Decision Systems.

Project work

You can use our award-winning take-home lab kits to explore core concepts at home. It supports our teaching, giving you the chance to learn by doing, when you want to, not just in classes. You’ll work on a major project of your own as part of your final assessment and there are chances to contribute to other projects throughout the course.

Teaching and assessment

You can expect a mix of lectures, tutorials, laboratory work and individual assignments. All the lectures and tutorials are for our systems and control students only. This helps you to bond with your fellow students, so you can learn from each other. You’re assessed on exams, coursework assignments and a project dissertation.

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The Advanced Computer Science (Computational Intelligence) MSc programme combines a wide choice of advanced topics in computer science with specialist modules relating to computational intelligence, including logic-based, connectionist and evolutionary artificial intelligence, inspirations from the natural world, practical applications and the philosophy of machine reasoning. Read more
The Advanced Computer Science (Computational Intelligence) MSc programme combines a wide choice of advanced topics in computer science with specialist modules relating to computational intelligence, including logic-based, connectionist and evolutionary artificial intelligence, inspirations from the natural world, practical applications and the philosophy of machine reasoning.

While studying a taught Master’s programme at the School of Computing, you can gain work experience through our industrial placement scheme or with the Kent IT Consultancy (KITC), which provides a project-based consultancy service to businesses in the region. We have strong links with industry including Cisco, IBM, Microsoft and Oracle and are among the top ten in the UK for graduate employment prospects.

The programme is aimed at graduates considering a career in research and development. It would also provide an excellent foundation for PhD study.

This programme is available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/249/advanced-computer-science-computational-intelligence

About the School of Computing

Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.

In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industrial Fellowships.

As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.

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.

CO885 - Project Research (15 credits)
CO880 - Project and Dissertation (60 credits)
CO881 - Object-Oriented Programming (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO884 - Logic and Logic Programming (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO846 - Cloud Computing (15 credits)
CO847 - Green Computing (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO545 - Functional and Concurrent Programming (15 credits)
CO641 - Computer Graphics and Animation (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO834 - Trust, Security and Privacy Management (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO889 - C++ Programming (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
CO894 - Development Frameworks (15 credits)
CO899 - System Security (15 credits)
PL583 - Philosophy of Cognitive Science and Artificial Intelligence (30 credits)

Assessment

Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation, except for the MSc in IT Consultancy for which the practical consultancy work is assessed through a series of reports covering each of the projects undertaken.

Programme aims

This programme aims to:

- enhance the career prospects of graduates seeking employment in the computing/IT sector

- prepare you for research and/or professional practice at the forefront of the discipline

- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)

- develop a variety of advanced intellectual and transferable skills

- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Careers

Students can gain practical work experience as part of their degree through our industrial placements scheme and Kent IT Consultancy. Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market.

Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

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

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If you wish to embark on an exciting career in the area of control systems and engineering or are a practising engineer who wishes to update their skills then this is the course for you. Read more
If you wish to embark on an exciting career in the area of control systems and engineering or are a practising engineer who wishes to update their skills then this is the course for you.

This is a challenging course which covers all the major aspects of automatic control systems engineering.

WHY CHOOSE THIS COURSE?

This course covers all the major aspects of automatic control systems engineering, with modules ranging from classical control system design to optimal, adaptive and intelligent control systems, including an introduction to artificial neural networks and evolutionary computing.

This Course has been awarded accreditations from the IET and InstMC.

WHAT WILL I LEARN?

All students study Seven fundamental modules which serve to underpin the remainder of the course:
-Maths & Computing for Control
-Linear Control Engineering
-Digital Computer Control Systems
-Non-Linear Control engineering
-System Identification, Parameter Estimation & Filtering
-Self-Tuning and Adaptive Control
-Control Systems Engineering Project

The remaining Option Topics on the course are:
-Digital Computer Control Systems;
-Simulation of Systems
-Data Acquisition and Embedded Control
-Signal and Image Processing
-Artificial Intelligence for Control
-Single Independent Study

(Students are required to select from the modules above to complete a total of 30 credits.)

In addition, the masters project can be tailored to suit the interests of each individual, and have included in the past: Adaptive model based control of a hot steel rolling mill; Comparison of rule-based and model based control systems; Identification of diesel engine characteristics from operating records and Development of a fuzzy logic gas engine speed controller.

HOW WILL THIS COURSE ENHANCE MY CAREER PROSPECTS?

On completion of this course you can expect to pursue a career in the area of control and systems engineering.

The course also provides the necessary groundwork for a career in research in academia or another such research organisation, including our own Control Theory and Applications Centre (CTAC) and Applied Mathematics Research Group (AMRC).

GLOBAL LEADERS PROGRAMME

To prepare students for the challenges of the global employment market and to strengthen and develop their broader personal and professional skills Coventry University has developed a unique Global Leaders Programme.

The objectives of the programme, in which postgraduate and eligible undergraduate students can participate, is to provide practical career workshops and enable participants to experience different business cultures.

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The Data Science and Computational Intelligence MSc has been designed to provide an industry-relevant programme that meets the needs of individuals wishing to pursue a research and development career in data science and computational intelligence. Read more
The Data Science and Computational Intelligence MSc has been designed to provide an industry-relevant programme that meets the needs of individuals wishing to pursue a research and development career in data science and computational intelligence.

Students will acquire knowledge, skills and expertise required for the analysis, interpretation and visualisation of complex, high-volume, high-dimensional and structured/unstructured data from varying sources. The programme will be delivered through activity-led and problem-based learning in the context of current research or industrial consultancy projects conducted by the academics teaching on the course. Students will explore cutting-edge research topics and technologies in order to maximise their professional career prospects.

The course has a carefully designed set of options that allows the individual to customise their programme of study according to their preferences, strengths and future plans.

WHY CHOOSE THIS COURSE?

If you choose this course you will benefit from the excellent modern facilities including specialist computing labs with high-performance hardware and industry-standard software. There will be opportunities for joint projects with local companies, guest lectures and interacting with employers. You will also have the opportunity to get involved in projects pursued by our research groups in: Computational Intelligence; Intelligent Information Modelling and retrieval; Distributed Systems and Modelling; Interactive Worlds; Digital Security and Forensics and Biomedical Computing and Engineering Technologies. Every year our students present their best work at the yearly Computing Show which attracts abundance of potential employers. You will work in collaborative international environment, which reflects the globalised nature of the computing industries. You can also get involved in variety of extra curricula activities including social events, trips and computing.

WHAT WILL I LEARN?

Mandatory study topics
-Artificial Neural Networks (15 credits)
-Machine Learning and Data Mining (15 credits)
-Fuzzy Logic and Evolutionary Computing (15 credits)
-Intelligent Information retrieval (15 credits)
-Business Intelligence and Big Data Processing (15 credits)
-Cloud Computing and Distributed Technologies (15 credits)
-Project dissertation (60 credits)

The remainder of the programme is bespoke, made up of topics from areas such as:
-IT Project Management (15 credits)
-Internet Systems Development (15 credits)
-Open Systems Application Development (15 credits)

The Data Science and Computational Intelligence postgraduate programme includes the completion of an individual project. Guided by an expert tutor, the MSc project serves to provide a method of applying previous learning whilst further developing the skills necessary to carry out research and facilitate the acquisition of valuable professional experience integral to that of a computer professional.

The MSc project serves to integrate and apply the subjects studied. The project could be industry-based or undertaken in collaboration with one of the University research groups, within the cognate area of this MSc.

HOW WILL THIS COURSE ENHANCE MY CAREER PROSPECTS?

The course presents existing opportunities in pursuing careers as data scientists, data professionals and data analysts in variety of sectors including financial services, retail, marketing, customer and business intelligence. On Completion of the course, graduates should be equipped with sought after, specialist knowledge and skills by industries which deal with very large volumes of data.

GLOBAL LEADERS PROGRAMME

Centre for Global Engagement logoTo prepare students for the challenges of the global employment market and to strengthen and develop their broader personal and professional skills Coventry University has developed a unique Global Leaders Programme.

The objectives of the programme, in which postgraduate and eligible undergraduate students can participate, is to provide practical career workshops and enable participants to experience different business cultures.

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Our research led MSc in Artificial Intelligence covers the fundamental aspects of traditional symbolic and sub-symbolic aspects. Read more

Our research led MSc in Artificial Intelligence covers the fundamental aspects of traditional symbolic and sub-symbolic aspects. This one year degree offers wide-ranging options including intelligent agents, complexity science, computer vision, robotics and machine learning techniques and helps develop a broad skill set suitable for further study or application development.

Introducing your degree

On this degree, you will learn from world-class researchers working in artifical intelligence fields such as computer vision, evolutionary computing, intelligent agents, game theory, deep learning and other machine learning methods. You will develop core data analysis skills and explore both traditional and state-of-the-art aspects of artificial intelligence and machine learning.

Overview

This research-led MSc takes a contemporary approach and covers the fundamental aspects of traditional symbolic and sub-symbolic aspects.

The programme will give you a solid awareness of the key concepts of artificial intelligence. You will also learn the techniques that form the current basis of machine learning and data mining. You will develop a wide-ranging skill set that supports further study or that you can use in application development.

As a result of the leading research being undertaken at Southampton, the course is able to offer a wide range of options that cover state-of-the-art modern techniques, which directly reflect research directions in ECS. These include:

  • intelligent agents
  • complexity science
  • computer vision
  • robotics
  • machine learning techniques, such as support vector machines and deep learning

View the programme specification document for this course

Career Opportunities

This programme provides an excellent platform for further research in either industry or academia.

Graduates from our MSc programme are employed worldwide in leading companies at the forefront of technology. ECS runs a dedicated careers hub which is affiliated with over 100 renowned companies like IBM, Arm, Microsoft Research, Imagination Technologies, Nvidia, Samsung and Google to name a few.

  • Academia
  • Bioinformatics
  • Chemoinformatics
  • Financial services
  • Web applications

Visit our careers hub for more information.



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This version of our flagship course includes a 12-month work placement. In the first year, you’ll take basic and advanced modules. Read more

About the course

This version of our flagship course includes a 12-month work placement. In the first year, you’ll take basic and advanced modules. In the second year, you’ll put your knowledge and skills to work.

We’ll give you training in research skills. You’ll carry out an extended research project with a dissertation. You’ll also write a report and give a presentation based on your work placement.

Push yourself further

We have cutting edge facilities and technology, including: advanced control
and systems software, modelling, simulation and controller design tools, robotics and a flexible manufacturing systems laboratory, evolutionary computing laboratory and clean facilities for the assembly of satellite instrumentation.

Make your mark

You could pursue a career with a large international organisation or government department. Our graduates work in sectors such as manufacturing, power generation and sustainable energy, with companies including British Airways, Jaguar Land Rover, NASA, IBM, Rolls-Royce and Unilever.

A masters from Sheffield is the mark of someone with the skills to apply their knowledge in industry, anywhere in the world. Our MSc in Advanced Control and Systems Engineering is accredited by the Engineering Council UK, IET and InstMC. These marks of assurance mean our degrees meet the high standards set by the engineering profession.

A Sheffield masters is a strong foundation for a career in industry or research.

Industry links

We have strong links with industrial partners such as Rolls-Royce and BAE Systems. Our industrial partners help us to design our courses, making sure you learn the right skills.

Rolls-Royce has a research and development centre here, using our expertise to explore today’s challenges. Our masters students often work side by side with researchers at these facilities.

A stimulating environment

The 2014 Research Excellence Framework (REF) rates us No 1 in the UK for research output, ahead of Oxford and Cambridge, and No 3 for overall research excellence. Our world-class reputation attracts highly motivated staff and students.

You’ll be taught by staff who work on real-world projects, developing new ideas – for submarines, robots, Formula One and even space exploration. Their approach to teaching is just as innovative: ideas like the award-winning take-home lab kit and e-puck mobile robotics activities help you develop the problem-solving skills you need for a trailblazing career.

Core Modules

Foundations of Control Systems; State-Space, Optimal Control and Nonlinear Systems; Signal Processing and Estimation; Embedded Systems and Rapid Control Prototyping; Managing Engineering Projects and Risk; Design Innovation Toolbox; Professional Responsibilities of the Engineer; Control Systems Project and Dissertation.

Examples of optional modules

Advanced Industrial Control; Robotic and Autonomous Systems; Intelligent and Vision Systems; Multisensor and Decision Systems; Nonlinear and Hybrid Systems.

Teaching and Assessment

There are lectures, tutorials, laboratory work and individual assignments. You will be assessed on examinations, coursework assignments and a project dissertation.

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This new course will not only teach you about the fundamental and advanced concepts of modelling, simulation, control, optimisation and systems engineering, but also provides you with a range of management techniques, including. Read more

About the course

This new course will not only teach you about the fundamental and advanced concepts of modelling, simulation, control, optimisation and systems engineering, but also provides you with a range of management techniques, including: project management, risk management, professional skills and effective management of innovative development.

Our world-leading research and our partnerships with industry give you an advantage in a competitive careers market. You’ll learn about the very latest developments in systems, control, computational intelligence and robotics – effectively preparing you for a future in engineering.

[Push yourself further]]

We have cutting edge facilities and technology, including: advanced control and systems software, modelling, simulation and controller design tools, robotics and a flexible manufacturing systems laboratory, evolutionary computing laboratory and clean facilities for the assembly of satellite instrumentation.

Make your mark

You could pursue a career with a large international organisation or government department. Our graduates work in sectors such as manufacturing, power generation and sustainable energy, with companies including British Airways, Jaguar Land Rover, NASA, IBM, Rolls-Royce and Unilever.

A masters from Sheffield is the mark of someone with the skills to apply their knowledge in industry, anywhere in the world. Our MSc in Advanced Control and Systems Engineering is accredited by the Engineering Council UK, IET and InstMC. These marks of assurance mean our degrees meet the high standards set by the engineering profession.

A Sheffield masters is a strong foundation for a career in industry or research.

Industry links

We have strong links with industrial partners such as Rolls-Royce and BAE Systems. Our industrial partners help us to design our courses, making sure you learn the right skills.

Rolls-Royce has a research and development centre here, using our expertise to explore today’s challenges. Our masters students often work side by side with researchers at these facilities.

A stimulating environment

The 2014 Research Excellence Framework (REF) rates us No 1 in the UK for research output, ahead of Oxford and Cambridge, and No 3 for overall research excellence. Our world-class reputation attracts highly motivated staff and students.

You’ll be taught by staff who work on real-world projects, developing new ideas – for submarines, robots, Formula One and even space exploration. Their approach to teaching is just as innovative: ideas like the award-winning take-home lab kit and e-puck mobile robotics activities help you develop the problem-solving skills you need for a trailblazing career.

Core Modules

Foundations of Control Systems; State-Space, Optimal Control and Nonlinear Systems; Signal Processing and Estimation; Embedded Systems and Rapid Control Prototyping; Managing Engineering Projects and Risk; Design Innovation Toolbox; Professional Responsibilities of the Engineer; Control Systems Project and Dissertation.

Examples of optional modules

Advanced Industrial Control; Robotic and Autonomous Systems; Intelligent and Vision Systems; Multisensor and Decision Systems; Nonlinear and Hybrid Systems.

Teaching and Assessment

There are lectures, tutorials, laboratory work and individual assignments. You will be assessed on examinations, coursework assignments and a project dissertation.

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This course will allow you to select leading classes that span the breadth of both computer and information sciences, including theoretical computer science, human-computer interaction, information sciences, software engineering, machine learning and big data. Read more
This course will allow you to select leading classes that span the breadth of both computer and information sciences, including theoretical computer science, human-computer interaction, information sciences, software engineering, machine learning and big data.

You’ll study

You'll gain an understanding of the new challenges posed by the advent of the big data revolution, particularly in relation to its modelling, storage, and access. You'll also come to understand the key algorithms and techniques embodied within data analytics solutions, and be exposed to a number of different big data technologies and techniques, seeing how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts.

You'll learn key technologies that are at the heart of big data analytics such as NoSQL databases and Hadoop and the Map-Reduce programming paradigm. You will also be equipped with a sound understanding of the principles of machine learning and a range of popular approaches, along with the knowledge of how and when to apply these.

You will also have the opportunity to implement and experiment with these machine learning algorithms using the most popular languages such as R and Python, and explore their applications to areas as diverse as analysing activity-related data captured using a smartphone to financial time-series prediction.

Individual project/dissertation

You’ll take on an individual research project on an approved topic related to your selected pathway. You’ll pursue a specific interest in further depth, giving scope for original thought, research and technical presentation of complex ideas.

Course content

Compulsory classes
-Legal, ethical and professional issues for the information society
-Distributed Information Systems
-Big Data Technologies
-Machine Learning for Data Analytics
-Research project

Elective classes - Choose two from the following:
-Advanced Topics in Software Engineering
-Mobile Software Applications
-Evolutionary Computing for Finance

Teaching methods include lectures, tutorials and practical laboratories. Dissertation is by supervision.

You’ll also have the opportunity to meet industry employers and participate in recruitment events.

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Researchers in the School of Biological Sciences conduct cutting-edge research across a broad range of biological disciplines. genomics, biotechnology, cell biology, sensory biology, animal behaviour and evolution, population biology, host-disease interactions and ecosystem services, to name but a few. Read more
Researchers in the School of Biological Sciences conduct cutting-edge research across a broad range of biological disciplines: genomics, biotechnology, cell biology, sensory biology, animal behaviour and evolution, population biology, host-disease interactions and ecosystem services, to name but a few.

In 2014 the school relocated to a new £54 million, state-of-the-art Life Sciences building. Our new laboratory facilities are among the best in the world, with critical '-omics' technologies and associated computing capacity (bioinformatics) a core component. The new building is designed to foster our already strong collaborative and convivial environment, and includes a world-leading centre for evolutionary biology research in collaboration with key researchers from earth sciences, biochemistry, social medicine, chemistry and computer sciences. The school has strong links with local industry, including BBC Bristol, Bristol Zoo and the Botanic Gardens. We have a lively, international postgraduate community of about 150 research students. Our stimulating environment and excellent graduate school training and support provide excellent opportunities to develop future careers.

Research groups

The underlying theme of our research is the search for an understanding of the function, evolution, development and regulation of complex systems, pursued using the latest technologies, from '-omics' to nanoscience, and mathematical modelling tools. Our research is organised around four main themes that reflect our strengths and interests: evolutionary biology; animal behaviour and sensory biology; plant and agricultural sciences; and ecology and environmental change.

Evolutionary Biology
The theme of evolutionary biology runs through all our research in the School of Biological Sciences. Research in this theme seeks to understand organismal evolution and biodiversity using a range of approaches and study systems. We have particular strengths in evolutionary genomics, phylogenetics and phylogenomics, population genetics, and evolutionary theory and computer modelling.

Animal Behaviour and Sensory Biology
Research is aimed at understanding the adaptive significance of behaviour, from underlying neural mechanisms ('how', or proximate, questions) to evolutionary explanations of function ('why', or ultimate, questions). The approach is strongly interdisciplinary, using diverse physiological and biomechanical techniques, behavioural experiments, computer modelling and molecular biology to link from the genetic foundations through to the evolution of behaviour and sensory systems.

Plant and Agricultural Sciences
The global issue of food security unifies research in this theme, which ranges from molecular-based analysis of plant development, signal transduction and disease, to ecological studies of agricultural and livestock production systems. We have particular strengths in functional genomics, bioinformatics, plant developmental biology, plant pathology and parasite biology, livestock parasitology and agricultural systems biology. Our research is helped by the LESARS endowment, which funds research of agricultural relevance.

Ecology and Environmental Change
Research seeks to understand ecological relations between organisms (plant, animal or microbe) at individual, population and community levels, as well as between organisms and their environments. Assessing the effect of climate change on these ecological processes is also fundamental to our research. Key research areas within this theme include community ecology, restoration ecology, conservation, evolutionary responses to climate change and freshwater ecology. Our research has many applied angles, such as ecosystem management, wildlife conservation, environmental and biological control, agricultural practice and informing policy.

Careers

Many postgraduate students choose a higher degree because they enjoy their subject and subsequently go on to work in a related area. An Office of Science and Technology survey found that around three-quarters of BBSRC- and NERC-funded postgraduates went on to a job related to their study subject.

Postgraduate study is often a requirement for becoming a researcher, scientist, academic journal editor and for work in some public bodies or private companies. Around 60 per cent of biological sciences doctoral graduates continue in research. Academic research tends to be contract-based with few permanent posts, but the school has a strong track record in supporting the careers of young researchers by helping them to find postdoctoral positions or develop fellowship applications.

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visit course pages for more information about the next Open Day at NHM on Wednesday 7 June 2017. Taxonomy and systematics provide the foundation for studying the great diversity of the living world. Read more

Open Day

visit course pages for more information about the next Open Day at NHM on Wednesday 7 June 2017.

Course Overview

Taxonomy and systematics provide the foundation for studying the great diversity of the living world. These fields are rapidly changing through new digital and molecular technologies. There is ever greater urgency for species identification and monitoring in virtually all the environmental sciences, and evolutionary ‘tree thinking’ is now applied widely in most areas of the life sciences.

This course provides in-depth training in the study of biodiversity based on the principles of phylogenetics, evolutionary biology, palaeobiology and taxonomy. The emphasis is on quantitative approaches and current methods in DNA-based phylogenetics, bioinformatics, and the use of digital collections.

Location

This course is a collaboration of Imperial College London (Silwood Park) with the Natural History Museum. This provides an exciting scientific environment of two institutions at the forefront of taxonomic and evolutionary research.

The MSc in Taxonomy and Biodiversity comprises two terms of taught modules, mostly based at the Natural History Museum, and covers core areas in biodiversity, palaeobiology, phylogenetics, molecular systematics, phylogenomics and taxonomic principles. This is followed by a 16-week laboratory or field-based research project at the NHM or Imperial College’s Silwood Park or South Kensington campuses.

Modules

• Taxonomy of major groups and the Tree-of-Life: An introduction of major branches of the Tree, including identification exercises, presented by NHM experts
• Statistics and Computing: A two-week intensive course at Silwood Park
• Field course: trapping and collecting techniques for terrestrial and aquatic ecosystems
• Phylogenetic Reconstruction: the principles of building phylogenetic trees
• Molecular Systematics: generating and analysing molecular data; model-based phylogenetics
• Phylogenomics: Genomic techniques for studying evolutionary processes and biodiversity
• Biodiversity (Concepts): speciation, radiation, macroevolution
•Biodiversity (Applied): Measuring biodiversity, geospatial analysis, collection management and biodiversity informatics
• Palaeobiology: Studying the fossil record and what we can learn for biodiversity

Post Study

Students on the course will become the new generation of taxonomists in the broadest sense. They will be familiar with these new tools, as well as the wider concepts of biodiversity science, evolutionary biology and genomics. Most importantly, students gain the abilities to work as an independent scientist and researcher, to be able to solve questions about the future of biodiversity and to communicate them to peers and the public.
Students have many options for future employment in evolutionary and ecological research labs in industry, government and non-governmental organisations, conservation, and scientific publishing and the media. The courses are an excellent starting point for PhD level careers, feeding into various Doctoral Training Programmes available at NHM and Imperial, or elsewhere.

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Anthropology prides itself on its inclusive and interdisciplinary focus. It takes a holistic approach to human society, combining biological and social perspectives. Read more
Anthropology prides itself on its inclusive and interdisciplinary focus. It takes a holistic approach to human society, combining biological and social perspectives.

All of our Anthropology Master’s programmes are recognised by the Economic and Social Research Council (ESRC) as having research training status, so successful completion of these courses is sufficient preparation for research in the various fields of social anthropology. Many of our students go on to do PhD research. Others use their Master’s qualification in employment ranging from research in government departments to teaching to consultancy work overseas.

We welcome students with the appropriate background for research. If you wish to study for a single year, you can do the MA or MSc by research, a 12-month independent research project.

If you are interested in registering for a research degree, you should contact the member of staff whose research is the most relevant to your interests. You should include a curriculum vitae, a short (1,000-word) research proposal, and a list of potential funding sources.

About the School of Anthropology and Conservation

Kent has pioneered the social anthropological study of Europe, Latin America, Melanesia, and Central and Southeast Asia, the use of computers in anthropological research, and environmental anthropology in its widest sense (including ethnobiology and ethnobotany).

Our regional expertise covers Europe, the Middle East, Central, Southeast and Southern Asia, Central and South America, Amazonia, Papua New Guinea, East Timor and Polynesia. Specialisation in biological anthropology includes forensics and paleopathology, osteology, evolutionary psychology and the evolutionary ecology and behaviour of great apes.

Course structure

The first year may include coursework, especially methods modules for students who need this additional training. You will work closely with one supervisor throughout your research, although you have a committee of three (including your primary supervisor) overseeing your progress. If you want to research in the area of applied computing in social anthropology, you would also have a supervisor based in the School of Computing.

Research areas

- Social Anthropology

The related themes of ethnicity, nationalism, identity, conflict, and the economics crisis form a major focus of our current work in the Middle East, the Balkans, South Asia, Amazonia and Central America, Europe (including the United Kingdom), Oceania and South-East Asia.

Our research extends to inter-communal violence, mental health, diasporas, pilgrimage, intercommunal trade, urban ethnogenesis, indigenous representation and the study of contemporary religions and their global connections.

We research issues in fieldwork and methodology more generally, with a strong and expanding interest in the field of visual anthropology. Our work on identity and locality links with growing strengths in customary law, kinship and parenthood. This is complemented by work on the language of relatedness, child health and on the cognitive bases of kinship terminologies.

A final strand of our research focuses on policy and advocacy issues and examines the connections between morality and law, legitimacy and corruption, public health policy and local healing strategies, legal pluralism and property rights, and the regulation of marine resources.

- Environmental Anthropology and Ethnobiology

Work in these areas is focused on the Centre for Biocultural Diversity. We conduct research on ethnobiological knowledge systems and other systems of environmental knowledge as well as local responses to deforestation, climate change, natural resource management, medical ethnobotany, the impacts of mobility and displacement and the interface between conservation and development. Current projects include trade in materia medica in Ladakh and Bolivia, food systems, ethno-ornithology, the development of buffer zones for protected areas and phytopharmacy among migrant diasporas.

- Digital Anthropology: Cultural Informatics, Social Invention and Computational Methods

Since 1985, we have been exploring and applying new approaches to research problems in anthropology – often, as in the case of hypermedia, electronic and internet publishing, digital media, expert systems and large-scale textual and historical databases, up to a decade before other anthropologists. Today, we are exploring cloud media, semantic networks, multi-agent modelling, dual/blended realities, data mining, smart environments and how these are mediated by people into new possibilities and capabilities.

Our major developments have included advances in kinship theory and analysis supported by new computational methods within field-based studies and as applied to detailed historical records; qualitative analysis of textual and ethnographic materials; and computer-assisted approaches to visual ethnography. We are extending our range to quantitative approaches for assessing qualitative materials, analysing social and cultural invention, the active representation of meaning, and the applications and implications of mobile computing, sensing and communications platforms and the transformation of virtual into concrete objects, institutions and structures.

- Biological Anthropology

Biological Anthropology is the newest of the University of Kent Anthropology research disciplines. We are interested in a diverse range of research topics within biological and evolutionary anthropology. These include bioarchaeology, human reproductive strategies, hominin evolution, primate behaviour and ecology, modern human variation, cultural evolution and Palaeolithic archaeology. This work takes us to many different regions of the world (Asia, Africa, Europe, the United States), and involves collaboration with international colleagues from a number of organisations. We have a dedicated research laboratory and up-to-date computing facilities to allow research in many areas of biological anthropology.

Currently, work is being undertaken in a number of these areas, and research links have been forged with colleagues at Kent in archaeology and biosciences, as well as with those at the Powell- Cotton Museum, the Budongo Forest Project (Uganda) and University College London.

Kent Osteological Research and Analysis (KORA) offers a variety of osteological services for human remains from archaeological contexts.

Careers

Higher degrees in anthropology create opportunities in many employment sectors including academia, the civil service and non-governmental organisations through work in areas such as human rights, journalism, documentary film making, environmental conservation and international finance. An anthropology degree also develops interpersonal and intercultural skills, which make our graduates highly desirable in any profession that involves working with people from diverse backgrounds and cultures.

Many of our students go on to do PhD research. Others use their Master’s qualification in employment ranging from research in government departments to teaching to consultancy work overseas.

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The Department of Zoology at UBC is internationally renowned for its research in a variety of modern biological sciences, including ecology, evolution, physiology, neurobiology, cell biology and development. Read more
The Department of Zoology at UBC is internationally renowned for its research in a variety of modern biological sciences, including ecology, evolution, physiology, neurobiology, cell biology and development. The department has many strong interdisciplinary connections between different areas of research.

Zoology has a solid computing infrastructure of computer labs, compute servers, loaner equipment, colour and poster printers, and three computing support staff for knowledgable help.

Program Overview

Zoology encompasses over 50 principal investigators. Research interests of faculty members can be divided into several broad categories with substantial overlap of interest and collaboration among these arbitrary groups. The program vigorously promotes integrative research in biology and actively participates in several interdisciplinary programs, including the graduate programs in genetics, neuroscience, applied mathematics, and resource management.

Zoology offers a wide variety of research programs leading to the Master of Science and Doctor of Philosophy in the following areas: cell and developmental biology, community and population ecology, comparative physiology and biochemistry, neurobiology, and evolutionary biology.

In addition Zoology is actively involved in several interdisciplinary programs of instruction and research including:
- Fisheries Centre
- Centre for Biodiversity Research
- Centre for Applied Conservation Research (CACR), Faculty of Forestry
- Genetics Program
- ICORD (International Collaboration on Repair Discoveries)
- Institute of Applied Mathematics
- BC Cancer Research Centre
- Life Sciences Institute

Quick Facts

- Degree: Master of Science
- Specialization: Zoology
- Subject: Life Sciences
- Mode of delivery: On campus
- Program components: Coursework + Thesis required
- Faculty: Faculty of Science

Research focus

- Cell and Developmental Biology: molecular and genetic bases of development and cellular function
- Comparative Physiology: aspects of animal physiology from a comparative perspective, particularly those mechanisms underlying adaptive responses to environmental constraints
- Ecology: blends field ecology and natural history with ecological theory and conservation biology
- Evolution: encompasses evolutionary ecology, evolutionary genetics, conservation genetics, theory, and systematics

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