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Masters Degrees (Computational Intelligence)

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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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About the course. Read more

About the course

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

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

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

Reasons to Study

• Internationally recognised reputation

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

• Benefit from our Research Expertise

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

• Flexible study options

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

• Dedicated robotics laboratory

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

• Employment Prospects

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

Course Structure

Modules

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

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

Teaching and Assessment

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

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

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

Contact and learning hours

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

Academic expertise

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

To find out more

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

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

Applying for a postgraduate course:

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

Funding for postgraduate students

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



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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
About the course. Read more

About the course

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

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

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

Reasons to Study

• Internationally recognised reputation

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

• Benefit from our Research Expertise

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

• Flexible study options

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

• Dedicated robotics laboratory

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

• Employment Prospects

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

Course Structure

Modules

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

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

Teaching and Assessment

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

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

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

Contact and learning hours

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

To find out more

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

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

Applying for a postgraduate course:

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

Funding for postgraduate students

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



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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)

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

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

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

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

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

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

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

Our expert staff

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

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

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

Specialist facilities

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

Your future

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

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

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

Example structure

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

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

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About the course. This course was developed and is run in conjunction with SAS, it will provide you with the knowledge and skills to effectively research, develop and apply business intelligence systems. Read more

About the course

This course was developed and is run in conjunction with SAS, it will provide you with the knowledge and skills to effectively research, develop and apply business intelligence systems. These are computerised information systems which support an organisation in the decision making process. Many of the techniques used in this area are underpinned by predictive statistics and mathematical modelling. This course will emphasise the concepts and techniques of business intelligence systems and their application and development. You will have access to specialist computing laboratories including one suite reserved specifically for postgraduate students. Upon graduating you be well placed to take up more general management and business information systems development roles within industry, or to undertake academic researchin this field.

Reasons to study:

• Taught by SAS accredited teaching staff

you will be taught by experienced SAS accredited teaching staff providing you with expert knowledge and skills allowing you to work toward your SAS accreditation

• SAS endorsed course

enhance your employability and gain substantial knowledge and skills in SAS business intelligence software leading towards SAS data miner accreditation

• 50 years history of research and teaching in computing technology

benefit from our well established academic expertise and advance your skills in, and knowledge of, developing business intelligence systems and data mining solutions to business problems

• Gain an insight into real world solutions

attend guest lectures and seminars, which will give you a real understanding of the impact of their work

• Excellent graduate prospects

graduates have gone into roles such as BI/SQL developers, logistics data modeller’s and insight analysts at organisations including Cognisco, LLamasoft and Occam DM

Course Structure

Modules

First semester

• Fundamentals of Business

Intelligence Systems

• Data Warehouse Design and OLAP

• Research Methods

• Statistics

Second semester

• Data Mining

• Business Intelligence Systems

Application and Development

• Analytics Programming

Plus two from the following list:

• Management of Information Systems

• Human Factors in Systems Design

• Applied Computational Intelligence

• Artificial Neural Networks

Third semester

• Final Project

Teaching and Assessment

Teaching will normally be delivered through formal lectures, informal seminars, tutorials, workshops, discussions and e-learning packages. Assessment will usually be carried out through a combination of individual and group work, presentations, reports, projects and exams.

Compulsory taught modules give you the opportunity to gain the fundamental knowledge and practices required to apply, develop and research business intelligence systems, while optional modules provide you with chances to study particular aspects of system application and development in more depth.

The individual project module allows you to undertake research into an aspect of business intelligence systems that interests you, and/or to perform appropriate business intelligence development tasks in response to a given practical problem.

Contact and learning hours

Full-time students will normally attend around 16 hours of timetabled taught sessions per week, and can expect to undertake around 24 further hours of self-directed independent study and research to support your assignments and dissertation.

Industry Association

This course was developed and is run in conjunction with SAS. SAS is the world's largest independent business analytics company. It provides an integrated set of software products and services to more than 45,000 customer sites in 118 countries. Across the globe, both the public and private sector use SAS software to assist in their efforts to compete and excel in a climate of unprecedented economic uncertainty and globalization.

To find out more

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

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

Applying for a postgraduate course:

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

Funding for postgraduate students:

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



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This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Read more

This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Practical machine-learning skill development is at the core of this programme, which is specifically designed to maximise employment potential across a wide spectrum of industrial and academic posts related to AI.

Artificial Intelligence is rapidly changing the way we live, work and learn. Both governments and industries have recognised the need for strategic development of AI -- technology giants such as Google, Microsoft and Facebook have each established their own AI research institutes, and the UK government recently announced its £75 million investment in the November 2017 Budget.

There is however a real shortage of AI talents worldwide, both to serve the industry and drive future research. Artificial Intelligence jobs are amongst the best paid in industry nowadays – an AI Specialist typically earns among the highest salaries (New York Times, 22nd Oct 2017), while having a solid AI background is strongly desired in multiple research disciplines.

MSc Artificial Intelligence importantly recognises such need for training cutting-edge AI talents, and is specifically designed to maximise student employability on AI-specific jobs.

This programme is:

• comprehensive: covering all five of the most popular AI topics

• up-to-date: each topic backed up by a world-leading group with cutting edge research

 unique: offering Game AI that represents some of the most advanced AI to date (e.g., AlphaGo)

• practical: focusing on developing practical machine-learning skills across all five AI topics

The programme brings together our teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine-learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.

Structure

MSc Artificial Intelligence is currently available for one year full-time study or two years part-time study.

Full-time (programme organised into three semesters)

Semester 1: Four modules that operate on a 3+1 scheme

3 core modules that cover the foundational machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).

Semester 2: Four modules themed around all five AI topics offered

The module selection allows students to focus on topic-specific research or industry applications for AI. More importantly, these module options allow students to gain advanced and up-to-date knowledge on selected AI topics.

Semester 3:

Students carry out a large project on the AI topic that they want to specialise in, after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.

Undertaking a masters programme is a serious commitment, with weekly contact hours in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching, independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.

Part-time

Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.

Important note regarding Part Time Study

We regret that due to complex timetabling constraints, we are not able to guarantee that lectures and labs for part time students will be limited to two days per week, neither do we currently support any evening classes. If you have specific enquiries about the timetabling of part time courses, please contact the MSc Administrator

Core modules:

·       Computational Intelligence and Games

·       Machine Learning

·       Data Mining

·       MSc Project module

Option modules:

·       Introduction to Computer Vision

·       Machine Learning for Visual Data Analysis

·       Deep Learning and Computer Vision

·       Music Perception and Cognition

·       Music and Speech Modelling

·       Music Analysis and Synthesis

·       Natural Language Processing

·       Advanced Natural Language Processing

·       Artificial Intelligence

·       Information Retrieval

·       Advanced Robotics Systems

·       Multi-platform Game Development

*All new courses are required to undergo a two-stage internal review and approval process before being advertised to students. Courses that are marked "subject to approval" have successfully completed the first stage of this process. Applications are welcome but we will not make formal offers for this course until it has passed this second (and final) stage.



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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.

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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.

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This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Read more

This programme aims at training those who would like to pursue a career in the booming field of Artificial Intelligence (AI). It uniquely covers all five of the hottest AI topics – games, robotics, vision, music, and language – each backed up by a respective research group at QMUL that is world-leading. Practical machine learning skill development is at the core of this programme, which is specifically designed to maximise employment potential across a wide spectrum of industrial and academic posts related to AI.

AI is rapidly changing the way we live, work and learn. Both governments and industry have recognised the need for strategic development of AI -- technology giants such as Google, Microsoft and Facebook have each established their own AI research institutes, and the UK government recently announced its £75 million investment in the November 2017 Budget.

There is however a real shortage of AI talents worldwide, both to serve the industry and drive future research. AI jobs are amongst the best paid in industry nowadays – an AI Specialist typically earns among the highest salaries (New York Times, 22nd Oct 2017), while having a solid AI background is strongly desired in multiple research disciplines.

MSc Artificial Intelligence importantly recognises such need for training cutting-edge AI talents, and is specifically designed to maximise student employability on AI-specific jobs.

This programme is:

  • comprehensive: covering all five of the most popular AI topics
  • up-to-date: each topic backed up by a world-leading group with cutting edge research
  • unique: offering Game AI that represents some of the most advanced AI to date (e.g., AlphaGo)
  • practical: focusing on developing practical machine learning skills across all five AI topics.

The programme brings together our teaching, research and industrial contacts to allow students to mix the different AI topics that best suits their personal requirements and future plans. Students will be offered lectures that explain the fundamental AI concepts, universal machine learning tools essential for any AI job profile, and specific practical and research skills on all five of the AI topics. Students will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL) via regular exercises and practical labs. Students will be taught by world-renowned academics in their specific subject areas, and have regular contacts with them throughout the duration of the programme.

Industrial Experience

The industrial placement takes place from the September following the taught part of the MSc for a maximum of 12 months. It is a student's responsibility to secure their own placement, but the EECS Placement Team will provide support. The Placement Team source and promote suitable opportunities, assist with applications, and with interview preparation.

The industrial placement consists of 8-12 months spent working with an appropriate employer in a role that relates directly to your field of study. The placement is currently undertaken after you have completed, passed the taught component of the degree and submitted your MSc project. The placement will provide the opportunity to apply key technical knowledge and skills gained from your taught modules and will enable you to gain a better understanding of your own abilities, aptitudes, attitudes and employment potential. The module is only open to students enrolled on a programme of study with integrated placement.

In the event that you are unable to secure a placement, we will transfer you onto the 1 year FT taught programme without the Industrial Experience. This change will also apply to any student visa you hold at the time.

Structure

MSc Artificial Intelligence is currently available for one year full-time study or two years part-time study.

Full-time (The programme is organised in three semesters)

Semester 1: Four modules that operate on a 3+1 scheme

3 core modules that cover the foundational machine learning techniques and introduction of Artificial Intelligence for Games (e.g., AlphaGo); and 1 optional module to select from three other AI topics (vision, music and language).

Semester 2: Four modules themed around all five AI topics offered

The module selection allows students to focus on topic-specific research or industry applications for AI. More importantly, these module options allow students to gain advanced and up-to-date knowledge on selected AI topics.

Semester 3:

Students carry out a large project on the AI topic that they want to specialise in, after agreeing on a specific topic with an academic supervisor in the first semester, and completing the preparation phase over the second semester.

Undertaking a masters programme is a serious commitment, with weekly contact hours being in addition to numerous hours of independent learning and research needed to progress at the required level. When coursework or examination deadlines are approaching independent learning hours may need to increase significantly. Please contact the course convenor for precise information on the number of contact hours per week for this programme.

Part-time

Part-time study options often mean that the number of modules taken is reduced per semester, with the full modules required to complete the programme spread over two academic years. Teaching is generally done during the day and part-time students should contact the course convenor to get an idea of when these teaching hours are likely to take place. Timetables are likely to be finalised in September but you may be able to gain an expectation of what will be required.

Core modules:

·       Computational Intelligence and Games

·       Machine Learning

·       Data Mining

·       MSc Project module

Option modules:

·       Introduction to Computer Vision

·       Machine Learning for Visual Data Analysis

·       Deep Learning and Computer Vision

·       Music Perception and Cognition

·       Music and Speech Modelling

·       Music Analysis and Synthesis

·       Natural Language Processing

·       Advanced Natural Language Processing

·       Artificial Intelligence

·       Information Retrieval

·       Advanced Robotics Systems

·       Multi-platform Game Development



*All new courses are required to undergo a two-stage internal review and approval process before being advertised to students. Courses that are marked "subject to approval" have successfully completed the first stage of this process. Applications are welcome but we will not make formal offers for this course until it has passed this second (and final) stage.



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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

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 ANC 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.



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On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling. Read more
On our MSc Algorithmic Trading, we equip you with the core concepts and quantitative methods in high frequency finance, along with the operational skills to use state-of-the-art computational methods for financial modelling.

We enable you to attain an understanding of financial markets at the level of individual trades occurring over sub-millisecond timescales, and apply this to the development of real-time approaches to trading and risk-management.

The course includes hands-on projects on topics such as order book analysis, VWAP & TWAP, pairs trading, statistical arbitrage, and market impact functions. You have the opportunity to study the use of financial market simulators for stress testing trading strategies, and designing electronic trading platforms.

In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas:
-Statistical and computational methods
-Modelling trading strategies and predictive services that are deployed by hedge funds
-Algorithmic trading groups
-Derivatives desks
-Risk management departments

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. We are supported by Essex’s highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.

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).

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.

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

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
-Big-Data for Computational Finance
-High Frequency Finance and Empirical Market Microstructure
-Introduction to Financial Market Analysis
-Professional Practice and Research Methodology
-Quantitative Methods in Finance and Trading
-Trading Global Financial Markets
-Cloud Technologies and Systems (optional)
-Constraint Satisfaction for Decision Making (optional)
-Creating and Growing a New Business Venture (optional)
-Digital Signal Processing (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Financial Engineering and Risk Management (optional)
-High Performance Computing (optional)
-Industry Expert Lectures in Finance (optional)
-Learning and Computational Intelligence in Economics and Finance (optional)
-Mathematical Research Techniques Using Matlab (optional)
-Programming in Python (optional)
-Text Analytics (optional)

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The Web Intelligence MSc aims to provide you with the knowledge and skills to solve challenging computational problems related to advanced reasoning systems for the internet. Read more

The Web Intelligence MSc aims to provide you with the knowledge and skills to solve challenging computational problems related to advanced reasoning systems for the internet. It will give you a broad understanding of web intelligence and a thorough knowledge of techniques for developing intelligent software. 

Key benefits

  • Located in central London giving access to major libraries and leading scientific societies, including the Chartered Institute for IT (BCS), and the Institution of Engineering and Technology (IET).
  • Opportunities to explore the fundamental roles and practical impacts of the use of artificial intelligence techniques in advanced computing.
  • Key study areas include fundamental internet technologies with complementary aspects of artificial intelligence, algorithmic issues on the web, and agents and multi-agent systems.
  • Frequent access to speakers of international repute through seminars and external lectures, enabling you to keep abreast of emerging knowledge in web intelligence and related fields.
  • The Department of Informatics has a reputation for delivering research-led teaching and project supervision from leading experts in their field.

Description

The Web Intelligence MSc will provide you with the practical knowledge and expertise to evaluate, design and build intelligent software for the internet. You will complete the course in one year, studying September to September and taking a combination of required and optional modules totalling 180 credits, including 60 credits that will come from a research project and dissertation of 10,000 words. You will study Artificial Intelligence, Agents and Multi-agent Systems as well as Software Engineering of Internet Systems. There are also opportunities to explore a broad range of optional modules allowing you to develop a study pathway that reflects your interests.

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

Teaching

We use lectures, seminars and group tutorials to deliver most of the modules on the programme. You will also be expected to undertake a significant amount of independent study.

You are expected to spend approximately 150 hours of effort (i.e. about 10 hours per credit) for each module you attend in your degree. These 150 hours cover every aspect of the module: lectures, tutorials, lab-based exercises, independent study based on personal and provided lecture notes, tutorial preparation and completion of exercises, coursework preparation and submission, examination revision and preparation, and examinations.

Assessment

The primary method of assessment for this course is a combination of written examinations, essays, coursework and individual or group projects and oral presentations. The research project will be assessed through a dissertation. 

Career prospects

Our graduates have continued on to have very successful careers in industry and research. Recent employers have included general software consultancy companies, specific software development businesses and the IT departments of large institutions (financial, telecommunications and public sector). Some graduates have entered into the field of academic and industrial research in software engineering, bio-informatics, algorithms, artificial intelligence and computer networks.



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

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

Our unique course covers the theoretical, applied and practical aspects of artificial intelligence, with an emphasis on:

- Genetic algorithms
- Evolutionary programming
- Fuzzy systems
- Neural networks
- Connectionist systems
- Hybrid intelligent systems

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

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

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