• University of Glasgow Featured Masters Courses
  • Swansea University Featured Masters Courses
  • University of York Featured Masters Courses
  • Regent’s University London Featured Masters Courses
  • Xi’an Jiaotong-Liverpool University Featured Masters Courses
  • Leeds Beckett University Featured Masters Courses
  • University of Leeds Featured Masters Courses
  • University of Edinburgh Featured Masters Courses
SOAS University of London Featured Masters Courses
Anglia Ruskin University Featured Masters Courses
University of Hertfordshire Featured Masters Courses
Imperial College London Featured Masters Courses
Loughborough University Featured Masters Courses
"computational" AND "inte…×
0 miles

Masters Degrees (Computational Intelligence)

  • "computational" AND "intelligence" ×
  • clear all
Showing 1 to 15 of 103
Order by 
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.

Read less
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

Read less
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/

Read less
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

Read less
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling. Read more
Our MSc Computational Finance equips you with the core concepts and mathematical principles of modern quantitative finance, plus the operational skills to use computational packages (mainly Matlab) for financial modelling.

We provide practical, hands-on learning about how modern, highly computerised financial markets work, how assets should be priced, and how investors should construct a portfolio of assets. In addition to traditional topics in derivatives and asset pricing, we place a special emphasis on risk management in non-Gaussian environment with extreme events.

You master these areas through studying topics including:
-Non-linear and evolutionary computational methods for derivatives pricing and portfolio management
-Applications of calculus and statistical methods
-Computational intelligence in finance and economics
-Financial markets

You also graduate with an understanding of the use of artificial financial market environments for stress testing, and the design of auctions and other financial contracts.

Our Centre for Computational Finance and Economic Agents is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.

Our research is geared towards real-world, practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.

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

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

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

Specialist facilities

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

Your future

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

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

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

Example structure

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

Read less
The Digital Media, Culture and Education MA explores the theory and practice of media education and emergent new literacies in the digital age. Read more
The Digital Media, Culture and Education MA explores the theory and practice of media education and emergent new literacies in the digital age. The programme combines theory with practical opportunities for media production. Students will critically examine new developments within digital media and work with partners including the British Film Institute (BFI).

Degree information

This programme provides the opportunity to explore media education, media literacy and related fields. It combines theory with practical opportunities in moving image production, Internet cultures and game design. Students will critically examine developments in the fields of new media, including the impact of new technologies on education, and debates about the place and purpose of media in society.

Students undertake modules to the value of 180 credits. The programme consists of two core modules (60 credits), two optional modules (60 credits), a dissertation (60 credits) or a report (30 credits) and an additional optional module (30 credits).

Core modules
-Digital Media, Cultural Theory and Education
-Internet Cultures: Theory & Practice

Recommended optional modules include:
-Moving Image Production
-Digital Games, Play and Creativity

Dissertation/report
All students undertake an independent research project, which culminates in a dissertation of 20,000 words or a report of 10,000 words.

Teaching and learning
Teaching is delivered by face-to-face lectures and seminars, practical workshops combined with online-learning. Students are assessed by coursework assignments of up to 5,000 words, plus practical work for some modules, and a 20,000-word dissertation or 10,000-word report.

Careers

Graduates of this programme are currently working across a broad range of areas. Some are working as teachers in primary, secondary schools and further and higher education, while others have jobs as within areas related to digital media. Graduates can also be found working as museum and gallery education officers and in other informal learning spaces.

Why study this degree at UCL?

This programme is run by UCL's London Knowledge Lab (LKL) where collaborating computer and social scientists research the future of learning with digital technologies in a wide range of settings. LKL conducts research, design and development across a broad range of media, systems and environments and brings together computer and social scientists from the areas of education, sociology, culture and media, semiotics, computational intelligence, information management, personalisation, semantic web and ubiquitous technologies.

Students are able to work with the BFI, our partner for one of our modules, as well as leading researchers from the DARE Collaborative, a research partnership focussed on the digital arts in education led by UCL Institute of Education (IOE) and the BFI.

LKL conducts research, design and development across a broad range of media, systems and environments and brings together computer and social scientists from the areas of education, sociology, culture and media, semiotics, computational intelligence, information management, personalisation, semantic web and ubiquitous technologies.

Read less
This intensive programme in data science and software engineering is designed for graduates who are new to computer science and provides an excellent grounding for working as a data scientist or analyst in industry. Read more
This intensive programme in data science and software engineering is designed for graduates who are new to computer science and provides an excellent grounding for working as a data scientist or analyst in industry. You will gain a broad knowledge of computing and acquire programming and data analysis skills, as well as comprehensive, practical problem-solving and analytical skills. You will also critically explore current research and methodologies and have the opportunity to investigate an area of current research in more depth via a project.

If you are new to computer science, this programme provides a solid foundation for a career in IT as a data scientist or analyst. For those already working in IT, the programme is an ideal opportunity to strengthen and update your knowledge and skills in the areas of data science and software engineering, while obtaining a formal Master's qualification.

This programme has been funded by the Higher Education Funding Council for England (HEFCE), as part of an innovative initiative to fund conversion courses in computing and engineering. This course uniquely enables students without any previous computer or data science experience at undergraduate level to study towards a Master's degree in this area of emerging importance. Crucially, the course covers both data science and software engineering, a combination of skills sought after in industry.

Why study this course at Birkbeck?

This programme is ideal if you are new to computer science and want to develop a career in IT as a data scientist or analyst.
Our Department of Computer Science and Information Systems is one of the longest-established in the world - we are celebrating our 60th anniversary in 2017.
We provide a stimulating teaching and research environment, with academic specialists in all fields, including information and knowledge management, web and pervasive technologies, computational intelligence, and information systems development, among others.
Our research dates back to the late 1940s, when one of the first electronic computers was developed at Birkbeck by Dr Andrew Booth. We now house the Computational Intelligence Research Group and the Information Management and Web Technologies Research Group, both of which collaborate with other research groups and with industry, in the UK and abroad, and undertake interdisciplinary research in the life, natural and social sciences, and the humanities.
We are also part of the London Knowledge Lab, a unique collaboration between Birkbeck and the UCL Institute of Education, which brings together computer and social scientists to explore how we learn, the role of technology in this process, and how technology relates to broader social, economic and cultural factors.
In the 2014 Research Excellence Framework (REF), more than 75% of our research outputs in Computer Science were ranked world-leading or internationally excellent.
You will have 24-hour access to several laboratories of networked PCs with a range of language compilers, database and other application software. We are connected, via the SuperJANET network, to the computers of other academic institutions in London, elsewhere in the UK and abroad.

Read less
The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. Read more

Research profile

The Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.

We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.

Our research falls into three areas:

-machine learning
-computational neuroscience
-computational biology

In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.

In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments

The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).

Training and support

You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.

A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.

The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.

Facilities

The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.

It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.

Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.

Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.

Career opportunities

The research you will undertake at IANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.

Read less
The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. Read more
The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. To improve the ability to solve a broad range of challenging computational problems related to advanced reasoning systems for the web by providing a thorough knowledge of techniques for developing intelligent software, and to provide a broad introduction to web intelligence.

Key benefits

• Web Intelligence has been recognised as a new direction for scientific research and development to explore the fundamental roles as well as practical impacts of the use of artificial intelligence techniques in advanced information technology.

• The programme will cover aspects of web intelligence through internet computing and the web on the one hand, and intelligent agent systems on the other.

• The strength of the programme is the integration of modules on fundamental internet technologies with the unique profile of the complementary aspects of artificial intelligence, algorithmic issues of the web, policies and norms, and agents and multi-agent systems that directly reflect our research expertise.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/web-intelligence-msc.aspx

Course detail

- Description -

This programme provides students with a broad understanding of web intelligence and a thorough knowledge of the techniques for developing intelligent software. It is built around taught core modules such as Agents and Multi-agent Systems, Artificial Intelligence and Software Engineering of Internet Applications, which are complemented by a wide range of optional modules that will broaden your understanding of web intelligence. The final part of the programme is an individual project which is closely linked with the Department's research activities.

- Course purpose -

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

- Course format and assessment -

Lectures; tutorials; seminars; laboratory sessions; optional career planning workshops. Assessed through: coursework; written examinations; final project report.

Career prospects

Via the Department’s Careers Programme, students are able to network with top employers and obtain advice on how to enhance career prospects. Our graduates have gone on to have very successful careers in industry and research. Recent employers have included general software consultancy companies, specialised software development companies and the IT departments of large institutions (financial, telecommunications and public sector). Other graduates have entered into the field of academic and industrial research in software engineering, bioinformatics, algorithms, artificial intelligence and computer networks.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

About Postgraduate Study at King’s College London:

To study for a postgraduate degree at King’s College London is to study at the city’s most central university and at one of the top 20 universities worldwide (2015/16 QS World Rankings). Graduates will benefit from close connections with the UK’s professional, political, legal, commercial, scientific and cultural life, while the excellent reputation of our MA and MRes programmes ensures our postgraduate alumni are highly sought after by some of the world’s most prestigious employers. We provide graduates with skills that are highly valued in business, government, academia and the professions.

Scholarships & Funding:

All current PGT offer-holders and new PGT applicants are welcome to apply for the scholarships. For more information and to learn how to apply visit: http://www.kcl.ac.uk/study/pg/funding/sources

Free language tuition with the Modern Language Centre:

If you are studying for any postgraduate taught degree at King’s you can take a module from a choice of over 25 languages without any additional cost. Visit: http://www.kcl.ac.uk/mlc

Read less
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).

Read less
This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

Read less
Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems. Read more

Overview

Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems.

As humans, we may be intrigued by the complexity of any daily activity. How do we perceive, act, decide, and remember? On the one hand, if we understand how our own intelligence works, we can use this knowledge to make computers smarter. On the other hand, by making computers behave more like humans, we learn more about how our own cognition works.

The AI Master’s programme at Radboud University has a distinctly cognitive focus. This cognitive focus leads to a highly interdisciplinary programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

See the website http://www.ru.nl/masters/ai

Scientific and practical applications

Slowly the human brain has been revealing its mystery to the scientific community. Now that we are actually able to model and stimulate aspects of cognition, AI researchers have gained a deeper understanding of cognition. At the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres, we train our students to become excellent researchers in this area.

At Radboud University we also teach students how to develop practical applications that will become the next generation of products, apps, therapies and services. Our department has been awarded several prizes for its pioneering role in bringing innovations from science to society, e.g. in Assistive Technology for people with disabilities. You’ll be taught the skills needed to conduct and steer such innovation processes. Many Master’s research projects have both a scientific and a practical component.

Specialisations

Computational modelling is the central methodology taught and used in this programme. Depending on the area of study, the computational models can range from behavioural models of millions of individuals interacting on the web, to functional models of human or robot decision-making, to models of individual or networks of artificial neurons. At Radboud University we offer the following three specialisations (on campus simply known as Computation, Robot and Web):

- Computation in Neural and Artificial Systems
Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.

- Robot Cognition
Understand all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.

- Web and Language Interaction
Learn how to build the intelligence used to power the future of the Web.

Research project and Internship

To finalise your AI master's programme, you have the choice of either an Internship (18EC) and Research Project (30EC) or a single larger Extended Research Project (48EC). During the internship you have the chance to acquire additional AI relevant skills either at a research lab or at a company. During the Research Projects phase, you get to put what you have learned during your master's programme into practice. You can perform your research work in the AI department, at other research departments at the University (e.g. the Behaviour Science Institute or Donders Institute) or at an external company (such as Philips or TNO). You are also encouraged to go abroad for your internship and/or research project (previously students have gone to Stanford University in California and Aldebaran Robotics in Paris). To help you decide on a thesis topic, there is an annual Thesis Fair where academics and companies present possible project ideas.

Job opportunities

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or a university with an AI department. Other graduates have started their own companies or work for companies interested in cognitive design and research.

Find out how to apply here http://www.ru.nl/masters/ai

Meet Radboud University

- Information for international students
Radboud University would like to meet you in your country (http://www.ru.nl/meetus) in order to give all the information you need and to answer any questions you might have about studying in the Netherlands. In the next few months, an advisor of Radboud University will be attending fairs in various countries, always accompanied by a current or former student.
Furthermore, we understand if you would like to see the Radboud Campus and the city of Nijmegen, which is why we organise an Master's Open Day for international students (http://www.ru.nl/openday) which will take place on 5 March 2016.

- Information for Dutch students
Radboud University offers students in the Netherlands plenty of opportunities to get more information on your programme of choice, or get answers to any questions you might have and more. Apart from a Master's Evening and a Master's Day, we also organise Orientation Days and a Master’s Afternoon for HBO students.

Read less
Our IT systems and devices are constantly creating data and the amount of data created and stored grows exponentially. Data, and in particular patterns and trends within data, have the ability to inform and provide valuable insights, that help us predict and diagnose specific outcomes. Read more
Our IT systems and devices are constantly creating data and the amount of data created and stored grows exponentially. Data, and in particular patterns and trends within data, have the ability to inform and provide valuable insights, that help us predict and diagnose specific outcomes. Whilst the amount of data grows, the science of gaining insights from this data grows with it. Industry, research institutions and government all seek to extract value from data to improve products and services, serve their customers better and run more operationally efficient organisations. Specialists in Business Intelligence use their mathematical, computational and presentational skills to mine data from enterprise information systems and elsewhere for value and their skills are highly sort after. There is a significant shortage of skilled Business Intelligence specialists and so there are many job opportunities available.

We have designed this MSc course in consultation with industry partners.

Having this close understanding of what industry needs makes this course relatively unique and the very best suited to those looking for a career in helping businesses to make better decisions.

The course will be of specific interest to :

A mathematics graduate wishing to use your skills in a vocational business based environment
A computer science graduate wishing to follow a vocational route
Individuals currently working in Business and looking to grow their career through gaining Data Science and Business Analytics skills
We have developed a number of modules to make up this MSc:

Business Intelligence Foundation
Managing Data and Data Warehousing
Data Exploration and Analysis
Statistics and Operational Research
Operations Management and Performance Improvement (option)
Data Visualisation and Presentation (option)
Business Decision Making (option)
The 1 year full time MSc course will be stimulating and interactive, making use of lectures, self-learning, workshops and hands-on projects.

You will be assigned a Personal Tutor from the start of your course who will work with you throughout your studies to help you achieve your academic best.

The knowledge we provide you with in these areas will give you all of the essential know-how on methods, tools and techniques to deliver in your career in Business Intelligence.

The modules will be focused on the practical application of theoretical concepts using a range of contemporary enterprise management knowledge systems.

The project work we have imbedded within the course has been chosen and developed based on real-world scenarios across a range of industry and government sectors and is specifically designed to:

Provide an essential link between your theoretical learning and real-world challenges
Create an environment where you decide the methods and tools best suited to the challenge based on what you have learnt
Recreate some of the challenges facing industry today and those very similar to what you will encounter in the workplace
Be adaptable to reflect new methods / tools and scenarios in this fast developing discipline
Be able upon completion of the projects to reference your experience in working with such challenges
Fees for 2017

Home fees - 1 year full-time: £8000.00

International fees: £10,920.00

Our facilities
You will undertake your workshops in training rooms that are bang up-to-date with design features, touch screen electronic white boards and high speed wifi; housed across three stunning Georgian mansions.

All of our current students love the learning environment, the culture, camaraderie and the fact that tutors know them by name so they are more than just a ‘face in the crowd’.

You will have access to the very best IT facilities in order to support your studies.

These range from computer labs to access to cloud analytics from the leading providers.

We will use software from the academic programs of the major enterprise I.T. vendors such as IBM and SAP as well as commonly used open source programs and frameworks.

From September 2018, many of the teaching sessions will take place in the purpose-built Engineering and Digital Technology building in the Bognor Regis campus.

What's more, you have lots of other facilities on this dedicated university campus including latest books, journals and online data in a truly modern library, an IT centre, a student zone complete with Costa Coffee, a gym and much more.

Where this can take you
The course has been designed to provide you with a very practical understanding of the issues associated with sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations. On completion of your MSc studies and successful graduation, you will have very transferable skills and can choose to move directly in to the workplace.

Indicative modules
Business Intelligence Foundation (20 Credits)
Managing Data and Data Warehousing (20 Credits)
Data Exploration and Analysis (20 Credits)
Statistics and Operational Research (20 Credits)
Operations Management and Performance Improvement (option) (20 Credits)
Data Visualisation and Presentation (option) (20 Credits)
Business Decision Making (option) (20 Credits)
Dissertation/Project (60 Credits)
Teaching and Assessment
Our approach to supporting your learning, and how your learning is assessed, is designed to mirror the workplace environment. With this in mind, key features of our approach to learning and assessment include the following:

We place a lot of emphasis on course work related activity.
Opportunities to work with organisations on current commercial/business problems and projects. These experiences are used to provide the basis for assessments that enable you to apply your learning within authentic commercial situations.

Read less
This taught postgraduate course is aimed at students who may not have studied computing exclusively but who have studied a considerable amount of computing already. Read more
This taught postgraduate course is aimed at students who may not have studied computing exclusively but who have studied a considerable amount of computing already.

If you want to become a specialist in a particular area of computing, this course will provide a first crucial step towards that goal.

This specialism focuses on artificial intelligence and knowledge engineering, and the development of computational and engineering models of complex cognitive and social behaviours.

Study areas include: cognitive robotics, complexity, complex systems, computational finance, computer networks, and distributed systems. We also offer specialisms in:

Computational Management Science
Machine Learning
Software Engineering
Secure Software Systems
Visual Information Processing

Each specialism has a flexible mix of breadth and depth, consisting of two or three compulsory modules as well as choices from a selection of core and optional modules.

You choose nine modules, seven of which must be selected from a group of eleven modules appropriate for the specialism.

Read less
This research led MSc incorporates traditional and state-of-the-art aspects of artificial intelligence (AI) and machine learning, through a contemporary approach which covers the fundamental aspects of traditional symbolic and sub-symbolic aspects. Read more

Course Summary

This research led MSc incorporates traditional and state-of-the-art aspects of artificial intelligence (AI) and machine learning, through a contemporary approach which covers the fundamental aspects of traditional symbolic and sub-symbolic aspects.

Modules

Semester one: Intelligent Agents; Machine Learning; Foundations of Artificial Intelligence; Computer Vision; Robotic Systems; Evolution of Complexity

Semester two: Advanced Computer Vision; Biological Inspired Robotics; Advanced Machine Learning; Advanced Intelligent Agents; Computational Biology; Computational Finance; Image Processing; Semantic Web Technologies; Simulation Modelling for Computer Science; Biometrics.

Plus three month independent research project culminating in a dissertation

Visit our website for further information...



Read less

Show 10 15 30 per page


Share this page:

Cookie Policy    X