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Masters Degrees in Artificial Intelligence, United Kingdom

We have 55 Masters Degrees in Artificial Intelligence, United Kingdom

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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
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)

Read less
The School has a strong international reputation for research in this area and this expertise influences this course which explores current research and practice in artificial intelligence and robotics. Read more
The School has a strong international reputation for research in this area and this expertise influences this course which explores current research and practice in artificial intelligence and robotics. This MSc can lead to a career such as a designer of intelligent systems or in research. The core modules are: artificial life with robotics, neural computation and machine learning, theory and practice of artificial intelligence.

Why choose this course?

-This MSc is available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies
-One of a range of advanced courses within our postgraduate Master's programme in Computer Science, this particular course provides you with a specialism in Artificial Intelligence and Robotics
-Advanced topics studied include artificial life with robotics, neural computation and machine learning, theory and practice of artificial intelligence
-Taught by a highly-regarded and long-established computer science department
-Sixty percent of our research impact in Computer Science and Informatics at the University of Hertfordshire has been rated at world-leading or internationally excellent in the Research Excellence Framework (REF) 2014

Careers

Our master's programme is designed to give Computer Science graduates the specialist, up-to-date skills and knowledge sought after by employers, whether in business, industry, government or research.

This particular course will prepare you to take up a challenging job or to pursue further research in specific AI fields. Typical career opportunities include researcher or designer for intelligent systems.

Teaching methods

Classes consist of lectures, small group seminars, and practical work in our well-equipped laboratories. We use modern, industry-standard software wherever possible. There are specialist facilities for networking and multimedia and a project laboratory especially for master's students.

In addition to scheduled classes, you will be expected a significant amount of time in self-study, taking advantage of the extensive and up-to-date facilities. These include the Learning Resource Centres, open 24x7, with 1,500 computer workstations and wifi access, Studynet our versatile online study environment usable on and off campus, and open access to our labs.

Work Placement

All our one year full time Computer Science Masters programmes are available with an optional one year industry placement. The 'with placement' programmes give you additional industrial experience by applying the skills you have learned throughout your studies.

They offer you the opportunity to work for one year in a highly professional and stimulating environment. You will be a full time employee in a company earning a salary and will learn new skills that can't be taught at University. During the placement, you will be able to gain further insight into industrial practice that you can take forward into your individual project.

We will provide excellent academic and personal support during both your academic and placement periods together with comprehensive careers guidance from our very experienced dedicated Careers and Placements Service.

Although the responsibility for finding a placement is with you, our Careers and Placements Service maintains a wide variety of employers who offer placement opportunities and organise special training sessions to help you secure a placement, from job application to the interview. Optional one-to-one consultations are also available.

In order to qualify for the placement period you must maintain an overall average pass mark of not less than 60% across all modules studied in semester ‘A’.

Structure

Year 1
Core Modules
-Professional Issues
-Investigative Methods for Computer Science
-Artificial Life with Robotics
-Neural Networks and Machine Learning
-Theory and Practice of Artificial Intelligence
-Preparation for Placement
-Professional Work Placement for MSc Computer Science

Optional
-Professional Issues
-Investigative Methods for Computer Science
-Data Mining
-Mobile Standards, Interfaces and Applications
-Human Computer Interaction: Principles and Practice
-Advanced Databases
-Programming Paradigms
-Measures and Models for Software Engineering
-Programming for Software Engineers
-Software Engineering Practice and Experience
-Distributed Systems Security
-Secure Systems Programming
-Network System Administration
-Multicast and Multimedia Networking
-Wireless, Mobile and Ad-hoc Networking
-Information Security, Management and Compliance
-Digital Forensics
-Penetration Testing

Year 2
Core Modules
-Artificial Intelligence with Robotics Masters Project

Read less
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.



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 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.



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

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

Introducing your degree

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

Overview

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

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

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

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

View the programme specification document for this course

Career Opportunities

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

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

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

Visit our careers hub for more information.



Read less
About the course. Read more

About the course

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

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

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

Reasons to Study

• Internationally recognised reputation

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

• Benefit from our Research Expertise

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

• Flexible study options

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

• Dedicated robotics laboratory

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

• Employment Prospects

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

Course Structure

Modules

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

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

Teaching and Assessment

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

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

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

Contact and learning hours

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

Academic expertise

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

To find out more

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

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

Applying for a postgraduate course:

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

Funding for postgraduate students

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



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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The MSc in Artificial Intelligence is a one-year taught programme run by the School of Computer Science. The course consists of two semesters of taught modules followed by an 11-week project leading to the submission of a 15,000-word dissertation in August. Read more

The MSc in Artificial Intelligence is a one-year taught programme run by the School of Computer Science. The course consists of two semesters of taught modules followed by an 11-week project leading to the submission of a 15,000-word dissertation in August.

Highlights

  • The MSc in Artificial Intelligence is a specialist course but retains some flexibility, allowing students to pursue other areas of computer science alongside the compulsory specialist modules. 
  • Students undertake a significant project, including a wide-ranging investigation and a substantial software development, leading to their dissertation, which enables them to consolidate and extend their specialist knowledge and critical thinking.
  • Students have 24-hour access to modern computing laboratories, provisioned with dual-screen PC workstations and group-working facilities.

Students on this course may switch to an MSc in Advanced Computer Science or in Information Technology after the first semester.

Teaching format

The taught portion of the MSc programme includes eight modules: five compulsory and three optional from a wide range available. Teaching methods include lectures, seminars, tutorials and practical classes. Most modules are assessed through practical coursework exercises and examinations. Class sizes typically range from 10 to 50 students. 

All students are assigned an advisor who meets with them at the start of the year to discuss module choices and is available to assist with any academic difficulties during the year. A designated member of staff provides close supervision for the MSc project and dissertation.

Further particulars regarding curriculum development.

Modules

The modules in this programme have varying methods of delivery and assessment. For more details of each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue which is for the 2017–2018 academic year; some elements may be subject to change for 2018 entry.



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The Need for Cybersecurity. Many of our societal infrastructures have been digital for quite some time, e.g. telecoms, banking, and e-commerce, and social media. Read more

The Need for Cybersecurity

Many of our societal infrastructures have been digital for quite some time, e.g. telecoms, banking, and e-commerce, and social media. The trend to increasing digitization continues apace, with areas such as health, power distribution, transport and manufacturing increasingly embracing the opportunities digitisation offers. In particular, the drive to increased automation and ‘smart’ operation inevitably means increased use computation.

The Internet of Things, perhaps the highest profile development in computing of recent times, marks a step change in connectivity, with some estimating 50 billion devices coming on-line by 2020. There is little doubt that we are hugely dependent on interconnected devices and systems and there are many opportunities to inflict malicious damage on them. Unsurprisingly, cybersecurity problems are reported in the media everyday. Cybersecurity is one of the most pressing problems of our day and securing computational systems and infrastructures is critical for healthy operation of modern societies.

Why Cybersecurity and Artificial Intelligence?


Artificial Intelligence (AI) has achieved an exceptional profile in recent years. If cybersecurity is one of the most pressing problems of our day then AI is perhaps the highest profile solution technology. Much ’smart’ infrastructure is underpinned by AI and the provision of insight via data analytics is becoming pervasive. Harnessing AI to provide more secure component and system designs and to provide insights into system operation, e.g. to detect intruders, is a natural goal.

AI underpins so much of the operation of modern day smart infrastructural and the AI algorithms and systems at the heart of such operation may themselves be maliciously attacked with great effect, e.g. the insertion of trapdoors into the neural networks that provide image recognition for automated car operation could cause catastrophic loss of life. Additionally, smart ‘attacks’ supported by AI means are now beginning to emerge; this introduces a new and worrying level of sophistication.

There is little doubt that AI will play a variety of offensive and defensive roles in the area of cybersecurity. Our MSc programme provides a grounding in cybersecurity fundamentals. It also provides a grounding in aspects of AI of significant relevance to cybersecurity, covering fundamental and widely applicable machine learning technologies, the computational support to use them, and specific data analytics technologies (text and speech processing).

Why Cybersecurtiy and Artificial Intelligence at Sheffield?

  • Be in demand - our course has been developed to meet acknowledged skills gaps.
  • Gain the specific skills increasingly valued by employers. Our programme has been developed with significant support from employers (who will also deliver the programme).
  • Access to a dedicated employability team to help increase your employment prospects.
  • Teaching informed by researchers working in relevant areas such as Cybersecurity, Machine Learning, Text and Natural Language Processing.
  • The Department of Computer Science is 5th in the UK for Research Excellence (REF 2014).


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

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

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

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

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

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Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent… Read more

Artificial Intelligence is a well-established, exciting branch of computer science concerned with methods to make computers, or machines in general, intelligent - so that they are able to learn from experience, to derive implicit knowledge from the one given explicitly, to understand natural languages such as English, Arabic, or Urdu, to determine the content of images, to work collaboratively together, etc. The techniques used in AI are as diverse as the problems tackled: they range from classical logic to statistical approaches to simulate brains.

This pathway reflects the diversity of AI in that it freely combines a number of themes related to AI techniques, namely Making Sense of Complex Data, Learning from Data, Reasoning and Optimisation, and Advanced Web Technologies.

Teaching and learning

Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.

Coursework and assessment

Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.

Facilities

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

Students following the Artificial Intelligence pathway have all the career choices and options as described for general Advanced Computer Science.

In addition, students of this pathway are ideally placed to work in positions requiring an understanding of modern AI formalism and technologies such as Natural Language Processing, Machine Learning, and Semantic Technologies. This includes the obvious positions in the games industry, but also positions in finance, commerce, and scientific research, and many more.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.



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This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world. Read more

This MSc is taught at the UK’s longest established centre for artificial intelligence, which remains one of the best in the world.

Our research draws on neuroscience, cognitive science, linguistics, computer science, mathematics, statistics and psychology to span knowledge representation and reasoning, the study of brain processes and artificial learning systems, computer vision, mobile and assembly robotics, music perception and visualisation. We aim to give you practical knowledge in the design and construction of intelligent systems so you can apply your skills in a variety of career settings.

Programme structure

You follow two taught semesters of lectures, tutorials, project work and written assignments, after which you will learn research methods before individual supervision for your project and dissertation.

Compulsory courses:

  • Informatics Research Review
  • Informatics Project Proposal
  • Introduction to Java Programming (for students who do not already meet the programming requirements for the taught masters)
  • Dissertation

You will choose a 'specialist area' within the programme, which will determine the choice of your optional courses:

  • Intelligent Robotics
  • Agents, Knowledge and Data
  • Machine Learning
  • Natural Language Processing

You can choose from a variety of optional courses including:

  • Advanced Vision
  • Algorithmic Game Theory and Its Applications
  • Machine Learning and Pattern Recognition
  • Natural Language Understanding
  • Robotics: Science and Systems
  • Human-Computer Interaction
  • Software Architecture, Process and Management
  • Text Technologies for Data Science
  • Computational Cognitive Neuroscience

Career opportunities

Our students are well prepared for both employment and academic research. The emphasis is on practical techniques for the design and construction of intelligent systems, preparing graduates to work in a variety of specialisms, from fraud detection software to spacecraft control.

Recent graduates are now working as software developers and engineers, programmers and data analysts for companies such as HarperCollins, J.P. Morgan, Nokia, IBM, Amazon, Soundcloud and the Bank of England.



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