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Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans. Read more
Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
On the one hand, the Master’s in Computation in Neural and Artificial Systems addresses how models based on neural information processing can be used to develop artificial systems, probing of human information processing in closed-loop online settings, as well as the development of new machine learning techniques to better understand human brain function.
On the other hand it addresses various ways of modelling and understanding cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics, complexity theory and optimal control theory to neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner. We also look at new groundbreaking areas in the field of AI, like brain computer interfacing and deep learning.

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

Why study Computation in Neural and Artificial Systems at Radboud University?
- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- Together with the world-renowned Donders Institute, the Behavioural Science Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.

- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.

Some examples of possible thesis subjects:
- Deep learning
Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.

- Brain Computer Interfacing
Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight (which mental states should we decode?) and technical expertise (which measurement systems and decoding algorithms should be used?). A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:
- PhD researcher on bio-inspired computing
- PhD researcher on neural decoding
- PhD researcher on neural information processing
- Machine learning expert in a software company
- Company founder for brain-based computer games
- Hospital-based designer of assistive technology for patients
- Policy advisor on new developments in neurotechnology
- Software developer for analysis and online visual displays of brain activity

Internship

Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Sweden and the United States.

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

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A flexible and interdisciplinary programme, which challenges you to use your specific knowledge to unravel the workings of the human brain. Read more
A flexible and interdisciplinary programme, which challenges you to use your specific knowledge to unravel the workings of the human brain.

Our brain contains many ingenious networks of millions of interconnected neurons. Together, they have a storage capacity and flexibility that far exceed modern supercomputers, or any artificial intelligent system. The Master’s specialisation in Neuroscience aims at unravelling the neuro-biological and neuro-computational mechanisms of this fascinating, complex system. We study the full spectrum from molecule to man, and from experiment to advanced theory and models.

The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.

Choose your own angle

Neuroscience at the Science Faculty ranges from biology to physics and mathematics, and will thus appeal to students from different Master’s programmes. The programme can be readily adapted to your individual academic background – whether that is in the field of Biology, Mathematics, Physics or Computing Science. Apart from fundamental knowledge of the brain, the Neuroscience specialisation also provides you with a general background in the principles of complex systems, and of intelligent behaviour of living and artificial systems.

Why study Neuroscience at Radboud University?

- Radboud University is the only university in the Netherlands that covers the complete research field of Neuroscience, from cognition to behaviour, and from sub-cellular processes, to single cell analysis and big data.
- The specialisation is closely connected to the world-renowned Donders Institute for Brain, Cognition and Behaviour (DI). You will get the chance to work with DI researchers during your internship, and build up a high profile network for your future career.
- The courses have a strong focus on research: they will cover the latest developments in brain research and technology, and train you the essential academic skills.
- You will work with students and researchers from different backgrounds in the natural sciences and become acquainted with a wide variety of research methods and scientific approaches.

Change perspective

The brain, as part of the human body, may at a first glance seem the exclusive domain of Biology. However, as the communication between neurons involves neurotransmitters and electrical ionic currents, understanding these mechanisms calls for knowledge of Chemistry and Physics. Moreover, studying mechanisms of coding and encoding of neural signals, requires advanced concepts from Mathematics and Informatics. By working together, our students learn to view complex issues from all these different sides.

Career prospects

Master’s specialisation in Neuroscience
The Master’s specialisation in Neuroscience gives you the chance to work at the Donders Institute for Brain, Cognition and Behaviour, and build up your own network of international renowned scientists who are working on the human brain: an excellent preparation for a future career in science. Neuroscience will also provide you with general skills that are required for any other job you aspire:
- the ability to structure complex problems
- excellent social skills for working in a multidisciplinary team
- extensive experience in presentations
- academic writing skills

Our approach to this field

At Radboud University, all branches of Neuroscience are accounted for, and strongly intertwined through the Donders Institute for Brain, Cognition and Behaviour (DI). This unique combination of expertises is a real advantage for Neuroscience students: it gives you absolute freedom to develop your knowledge in your field of interest and a high profile network for your future career.

- Science faculty
In this specialisation at the Science faculty, you will use your background in the natural sciences to unravel neurobiological processes. When completed, you will receive a Master’s degree in Medical Biology, Molecular Life Sciences, Physics & Astronomy or Science. For highly talented students it is possible to obtain a second Master’s degree at the selective Research Master’s in Cognitive Neuroscience of the DI, which has a more cognitive approach. This extra Master’s degree takes one additional year (60 EC) to complete.

- Themes
The Master’s specialisation in Neuroscience focuses on three of the four research themes of the Donders Institute for Brain, Cognition and Behaviour:

- Perception, Action and Control
Focus: Studying sensorimotor mechanisms, their cognitive and social components, their clinical implications, and their relevance for robotics.

Research: Researchers use theoretical analysis, psychophysical and behavioural studies, neurophysiological techniques, neuroimaging, clinical and pharmacological interventions, developmental and genetic approaches.

- Plasticity and Memory
Focus: The development and decay of the healthy and the maladaptive brain.

Research: Researchers in this field study the mechanistic underpinnings and behavioural consequences of long-term changes in neural structure and function. Genetic, molecular and cellular methods, animal models, as well as human neuroimaging and cognitive neuropsychology are used.

- Brain Networks and Neuronal Communication
Focus: Complex neural networks, ranging from the very smallest – communication between individual neurons – to the largest: communication between different brain areas and the outside world.

Research: The research groups combine the development of new techniques for measurements of connectivity and activation, with the experimental application of these techniques in studies of cognition in humans, non-human primates and rodents. Computational modelling is an important component.

- Custom approach
The specialisation programme depends on the Master’s programme that you will follow. In this way, it will perfectly fit to your current knowledge and practical skills. However, as all neuroscience research topics are interdisciplinary, you will become acquainted with other disciplines as well. This will help you to develop a common ground that is necessary to communicate in a multi-faceted (research) team.

See the website http://www.ru.nl/masters/medicalbiology/neuro

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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

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Computer security remains a hot topic in the media and there is strong demand for graduates with technical skills in this area. The programme addresses computer and information security holistically because vulnerability in any one component can compromise an entire system. Read more
Computer security remains a hot topic in the media and there is strong demand for graduates with technical skills in this area. The programme addresses computer and information security holistically because vulnerability in any one component can compromise an entire system.

This includes computer architectures, operating systems, network technologies, data storage and software development processes. A wide range of threats and other security issues (for example, denial-of-service attacks, hacking, viruses and worms) are covered along with defences and countermeasures.

The programme is aimed at computing graduates who are seeking careers as computer security professionals or who are interested in research. All taught Master’s programmes at Canterbury are available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/254/computer-security

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.

CO834 - Trust, Security and Privacy Management (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO880 - Project and Dissertation (60 credits)
CO885 - Project Research (15 credits)
CO899 - System Security (15 credits)
CO894 - Development Frameworks (15 credits)
CO889 - C++ Programming (15 credits)
CO846 - Cloud Computing (15 credits)
CO882 - Advanced Object-Oriented Programming (15 credits)
CO883 - Systems Architecture (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO545 - Functional and Concurrent Programming (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO847 - Green Computing (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
EL846 - Industrial Context of Biometrics (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO881 - Object-Oriented Programming (15 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.

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 KITC (see above). Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market. Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

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

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Computer science is the study of theoretical foundations and practical techniques for implementation in computer systems. Despite its short history, computer science has made major contributions to science and society that have transformed the way we live our lives. Read more
Computer science is the study of theoretical foundations and practical techniques for implementation in computer systems. Despite its short history, computer science has made major contributions to science and society that have transformed the way we live our lives.

There are many sub-fields of computer science and this course provides an opportunity to study a range of these to an advanced level, with a particular emphasis on application development,network security and artificial intelligence.

You will be taught by an internationally recognised team, drawn from the University’s Centre of Excellence in Mobile Applications and Services (CEMAS), the Computer Science and Artificial Intelligence Paradigms research unit (CSAIP) and the Information SecurityResearch Group.

See the website http://courses.southwales.ac.uk/courses/252-msc-computer-science

What you will study

- Real-time Computer Graphics
- Software Development
- Network Security
- Mobile Application Development
- Neural Networks
- Expert Systems
- Professional Skills Development
- Advanced Research Methods
- Project Management
- Research Project: an investigation of your choice, related to the course
- MSc Project: the development and evaluation of a significant application or task of your choice, related to the course.

Learning and teaching methods

The course is delivered in four major blocks that offer an intensive but focused learning pattern, with two entry opportunities for applicants every year – February and September. Full-time students will typically spend 12 hours in classes each week. If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects. You need to spend a significant amount of time working independently, reading and preparing for assessments.

Work Experience and Employment Prospects

The skills developed on this course strongly relate to the role of a software developer in a range of specialised areas. For example, business analytics for optimisation is one of the key areas highlighted by e-skills, and this course provides an opportunity to develop knowledge and skills at the forefront of this field, in addition to practical programming elements.

Students who complete this award will be educated to a professional standard in a range of fields related to computer science, and will have improved transferable skills. These include problem solving, communication, team working, effective use of IT facilities and information retrieval.

With training to Masters level now the recognised professional level of competence, graduates will be better placed to pursue careers in industry, or continue their interest in computer science through research at PhD level.

Assessment methods

You will be assessed primarily by coursework. You will work on a significant research project and major project of your choice, where strong independent thinking, critical analysis and project management skills will be important.

Facilities

We have a full range of high-specification computer labs and an ongoing investment programme to ensure that our facilities stay at the forefront of computing developments.

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Be inspired to innovate and develop the robots, artificial intelligence and autonomous systems of tomorrow’s world. Read more
Be inspired to innovate and develop the robots, artificial intelligence and autonomous systems of tomorrow’s world. Gain advanced theoretical and practical knowledge from our world-leading experts in interactive and intelligent robotics, and graduate ready to pursue an exciting career in anything from home automation to deep sea or space exploration. You’ll also have the opportunity to gain invaluable industry experience and cultivate professional contacts on an integral work placement.

Key features

-Enhance your employability and grow your professional network with an optional integral work placement. You can choose to work in the UK, or overseas in countries including France, Germany or Japan.
-Get up-to-date with the latest developments in artificial life and intelligence, adaptive behaviour, information visualisation, neural computation and dynamic systems, as well as remote access and monitoring systems. Our seminars series with speakers from industry and academia gives you the opportunity to keep ahead in this fast moving field.
-Give yourself the edge. Our programme distinguishes itself from other robotics masters programmes, in the UK and abroad, by ensuring a deeper theoretical and practical knowledge of interactive and intelligent robotics.
-Expand your skills with first-class facilities including 3D rapid prototyping systems, in-house PCB design and assembly tools, and our award winning Plymouth Humanoid robots.
-Get expert training from members of the Marine and Industrial Dynamic Analysis (MIDAS) research group and the Centre for Robotics and Neural Systems (CRNS).
-Become a professional in your field – this programme is accredited by the Institution of Engineering and Technology (IET).
-Benefit by combining disciplines that are traditionally taught separately. You’ll graduate ready with the expertise and joined-up knowledge to design and develop fully integrated mechanical, electronic, control and computing systems.

Course details

On this programme you’ll gain a solid and broad understanding of the latest developments and issues in robotics. You’ll build theoretical and practical knowledge of control and design as well as covering the interface between real-world devices, autonomous processing and evaluation of acquired information. You’ll investigate user interaction and intelligent decision-making and immerse yourself in an innovative project inspired by the latest developments in technology and society. You’ll have access to a robotics club and to a seminar series so that you can keep up-to-date with advances in the industry and academia.

Core modules
-ROCO503 Sensors and Actuators
-BPIE500 Masters Stage 1 Placement Preparation
-PROJ509 MSc Project
-AINT511 Topics in Advanced Intelligent Robotics
-MECH533 Robotics and Control
-SOFT561 Robot Software Engineering
-AINT513 Robotic Visual Perception and Autonomy
-AINT512 Science and Technology of Human-Robot Interaction

Optional modules
-BPIE502 Electrical/Robotics Masters Industrial Placement

Every postgraduate taught course has a detailed programme specification document describing the programme aims, the programme structure, the teaching and learning methods, the learning outcomes and the rules of assessment.

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One of a range of degrees from the taught Master's Programme at the School of Computer Science. This course considers current research and practice in computer networking, distributed systems and security. Read more
One of a range of degrees from the taught Master's Programme at the School of Computer Science.

About the course

This course considers current research and practice in computer networking, distributed systems and security. You will develop technical expertise and practical skills in the design, management and evaluation of networks, and in the use of tools and techniques for system security.

This MSc can lead to a career such as a network system designer or administrator, or as a security consultant.

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 combining theoretical knowledge and practical skills in computer networking
-You will develop technical expertise and practical skills in the design,management and evaluation of networks, and in the use of tools and techniques for system security
-Taught by a highly-regarded and long-established computer science department with strong links to business
-Half the research outputs in Computer Science at the University of Hertfordshire have been rated at world-leading or internationally excellent in the Research Excellence Framework (REF) 2014

Careers

Our masters 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 for a career such as a software engineer, developer or project manager.

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 masters 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

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.

This offers 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
-Distributed Systems Security
-Secure Systems Programming
-Network System Administration
-Multicast and Multimedia Networking
-Wireless, Mobile and Ad-hoc Networking
-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
-Artificial Life with Robotics
-Neural Networks and Machine Learning
-Theory and Practice of Artificial Intelligence
-Information Security, Management and Compliance
-Digital Forensics
-Penetration Testing

Year 2
Core Modules
-Computer Networking Principles and Practice Masters Project

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This flexible course offers a largely free choice of modules from our range of Advanced Master's programmes. It is likely to appeal to computing graduates whose interests span more than one specialism and/or those seeking the freedom to explore a variety of advanced topics. Read more
This flexible course offers a largely free choice of modules from our range of Advanced Master's programmes.

It is likely to appeal to computing graduates whose interests span more than one specialism and/or those seeking the freedom to explore a variety of advanced topics. Depending on the options chosen, this course can serve as a springboard for employment or research.

This programme is available with an optional industrial placement. The course duration varies depending on the options taken.

Visit the website https://www.kent.ac.uk/courses/postgraduate/246/advanced-computer-science

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 Industry 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.

CO880 - Project and Dissertation (60 credits)
CO885 - Project Research (15 credits)
CO881 - Object-Oriented Programming (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO846 - Cloud Computing (15 credits)
CO882 - Advanced Object-Oriented Programming (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO889 - C++ Programming (15 credits)
CO894 - Development Frameworks (15 credits)
CO899 - System Security (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (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)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO834 - Trust, Security and Privacy Management (15 credits)
CO884 - Logic and Logic Programming (15 credits)
CO847 - Green Computing (15 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.

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 KITC (see above). 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
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
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling… Read more
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations, from retailers such as Tesco or Amazon, to manufacturers like BMW, to health-care providers, and to public administration.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscdatascienceandanalytics.aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will acquire both the foundational knowledge and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations from retailers such as Tesco or Amazon, to manufacturers like BMW, health-care providers, or public administration. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning – the science behind ‘Big Data’ – is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liason Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).
Please visit our websitefor additional information on this degree.

On completion of the course graduates will have:
- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant. Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling… Read more
This degree, offered by the Department of Computer Science, will teach you both the foundational aspects and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations, from retailers such as Tesco or Amazon, to manufacturers like BMW, to health-care providers, and to public administration.

As part of the course, you will take an industrial placement, where you will gain valuable experience by putting your knowledge and skills into practice.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscdatascienceandanalytics(yearinindustry).aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will acquire both the foundational knowledge and the practical skills that prepare you for handling and analysing different types of data in different fields, thus responding to the needs of a huge variety of companies and organisations from retailers such as Tesco or Amazon, to manufacturers like BMW, health-care providers, or public administration. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Taking a placement is an excellent opportunity to gain industrial experience (which gives you an extra edge when applying for jobs in the future) and acquire skills that can only be fully picked up in a work environment.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning – the science behind ‘Big Data’ – is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

Your placement will take up to one year and, if you are an overseas student, your visa will cover the two years of the programme. The placement attracts a salary and is assessed as part of your degree. You will be assigned a supervisor by the host company, who is responsible for directing your work. You will be assigned an academic supervisor, who visits to check if you are integrating successfully and the type of work being undertaken is appropriate, and supports you in general during your placement. If you cannot or decide not to take a placement, you revert to the normal one-year degree.

On completion of the course graduates will have:
Throughout your degree, you will have the opportunity to acquire the following skills:

- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.
- Work experience and appreciation of how your work fits into the organizational and development processes of a company.

Assessment

Assessment is carried out by a variety of methods including coursework, examinations and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant.

Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies. Read more
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscmachinelearning.aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will gain in-depth knowledge and practical skills in Machine Learning techniques, which are used by companies such as Facebook, Google, Microsoft and Yahoo to develop the next generation of search and analysis technologies. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

On completion of the course graduates will have:
- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant. Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies. Read more
This degree, offered by the Department of Computer Science, allows you to develop a deeper understanding of Machine Learning – the science of systems that can learn from data – which companies such as Facebook, Google, Microsoft and Yahoo require to create, innovate, and define the next generation of search and analysis technologies.

As part of the course, you will take an industrial placement, where you will gain valuable experience by putting your knowledge and skills into practice.

See the website https://www.royalholloway.ac.uk/computerscience/coursefinder/mscmachinelearning(yearinindustry).aspx

Why choose this course?

- Big Data is now part of every sector and function of the global economy. Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.

- You will gain in-depth knowledge and practical skills in Machine Learning techniques, which are used by companies such as Facebook, Google, Microsoft and Yahoo to develop the next generation of search and analysis technologies. People with this set of skills are in short supply and high demand.

- You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.

- You will also be well prepared to pursue studies at PhD level, which several companies prefer for their research laboratories and more advanced roles.

- Taking a placement is an excellent opportunity to gain industrial experience (which gives you an extra edge when applying for jobs in the future) and acquire skills that can only be fully picked up in a work environment.

- Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.

- Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.

- Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best: in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world.

Department research and industry highlights

- The excellence of our research in Machine Learning is recognized worldwide, and the topics taught reflect that excellence.

- In the most recent Research Assessment Exercise (RAE 2008), the Department ranked 11th among UK Computer Science departments for its research output.

- The Department is ranked third in the UK for graduate employability by the Times Good University Guide 2013.

- The Department has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft.

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

On completion of the course graduates will have:
- A highly analytical approach to problem solving.
- A strong background in data modelling and business intelligence.
- Knowledge of computational and statistical data analysis.
- A background in machine learning, statistics, and data mining.
- Ability to develop, validate, and use effectively machine learning models and statistical models.
- Ability to apply machine learning and data mining techniques to Information Retrieval and Natural Language Processing.
- Knowledge of and ability to work with software to automate tasks and perform data analysis.
- Knowledge of and ability to work with structured, unstructured, and time-series data.
- Ability to extract value and insight from data.
- Knowledge of and ability to work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, neural networks.
- Appreciation and knowledge of non-statistical approaches to data analysis and machine learning.
- Ability to work with software packages such as MATLAB and R.
- Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques.
- Knowledge of and ability to work with Python, Perl, and Shell Scripting.
- Work experience and appreciation of how your work fits into the organizational and development processes of a company.

Assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are among the most employable in the UK – we rank third in the UK for graduate employability – and, in recent years, have entered many different Computer Science-related roles including network systems design and engineering, web development and production. Other graduates choose to enter careers with a management or financial slant. Our graduates have found employment at a wide range of organisations including Logica, British Telecom, British Aerospace, Microsoft, Amazon.com, American Express, Sky and Orbis Technology. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to the Department. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online https://www.royalholloway.ac.uk/studyhere/postgraduate/applying/howtoapply.aspx .

Read less
An MSc-level conversion programme for those with first degrees in numerate disciplines (e.g. Maths, Physics, others with some mathematics to pre-university level should enquire). Read more
An MSc-level conversion programme for those with first degrees in numerate disciplines (e.g. Maths, Physics, others with some mathematics to pre-university level should enquire). The programme targets producing engineers with the knowledge and skills required for working in the communications industry on programmable hardware, in particular. There is a high demand for people to fill such roles in communications and test & measure equipment vendors, and in many smaller companies developing devices for the internet of things.

The huge growth of interconnected devices expected in the Internet of Things and the goals of flexible, high-speed wireless connections for 5G mobile networks and beyond, require programmable, embedded electronics to play a vital role. From the development of small, intelligence sensors to the design of large-scale network hardware that can be functionally adaptive in software-defined networking, there is a huge demand for advanced embedded electronics knowledge and skills in the communications sector.

Visit the website https://www.kent.ac.uk/courses/postgraduate/1223/embedded-communications-engineering

About the School of Engineering and Digital Arts

The School of Engineering and Digital Arts successfully combines modern engineering and technology with the exciting field of digital media.

Established over 40 years ago, the School has developed a top-quality teaching and research base, receiving excellent ratings in both research and teaching assessments.

The School undertakes high-quality research that has had significant national and international impact, and our spread of expertise allows us to respond rapidly to new developments. Our 30 academic staff and over 130 postgraduate students and research staff provide an ideal focus to effectively support a high level of research activity. There is a thriving student population studying for postgraduate degrees in a friendly and supportive teaching and research environment.

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.

EL829 - Embedded Real-Time Operating Systems (15 credits)
EL849 - Research Methods & Project Design (30 credits)
EL893 - Reconfigurable Architectures (15 credits)
EL896 - Computer and Microcontroller Architectures (15 credits)
EL822 - Communication Networks (15 credits)
EL827 - Signal & Communication Theory II (15 credits)
EL871 - Digital Signal Processing (DSP) (15 credits)
EL872 - Wireless/Mobile Communications (15 credits)
EL873 - Broadband Networks (15 credits)
EL890 - MSc Project (60 credits)

Research areas

- Communications

The Group’s activities cover system and component technologies from microwave to terahertz frequencies. These include photonics, antennae and wireless components for a broad range of communication systems. The Group has extensive software research tools together with antenna anechoic chambers, network and spectrum analysers to millimetre wave frequencies and optical signal generation, processing and measurement facilities. Current research themes include:

- photonic components
- networks/wireless systems
- microwave and millimetre-wave systems
- antenna systems
- radio-over-fibre systems
- electromagnetic bandgaps and metamaterials
- frequency selective surfaces.

- Intelligent Interactions:

The Intelligent Interactions group has interests in all aspects of information engineering and human-machine interactions. It was formed in 2014 by the merger of the Image and Information Research Group and the Digital Media Research Group.

The group has an international reputation for its work in a number of key application areas. These include: image processing and vision, pattern recognition, interaction design, social, ubiquitous and mobile computing with a range of applications in security and biometrics, healthcare, e-learning, computer games, digital film and animation.

- Social and Affective Computing
- Assistive Robotics and Human-Robot Interaction
- Brain-Computer Interfaces
- Mobile, Ubiquitous and Pervasive Computing
- Sensor Networks and Data Analytics
- Biometric and Forensic Technologies
- Behaviour Models for Security
- Distributed Systems Security (Cloud Computing, Internet of Things)
- Advanced Pattern Recognition (medical imaging, document and handwriting recognition, animal biometrics)
- Computer Animation, Game Design and Game Technologies
- Virtual and Augmented Reality
- Digital Arts, Virtual Narratives.

- Instrumentation, Control and Embedded Systems:

The Instrumentation, Control and Embedded Systems Research Group comprises a mixture of highly experienced, young and vibrant academics working in three complementary research themes – embedded systems, instrumentation and control. The Group has established a major reputation in recent years for solving challenging scientific and technical problems across a range of industrial sectors, and has strong links with many European countries through EU-funded research programmes. The Group also has a history of industrial collaboration in the UK through Knowledge Transfer Partnerships.

The Group’s main expertise lies primarily in image processing, signal processing, embedded systems, optical sensors, neural networks, and systems on chip and advanced control. It is currently working in the following areas:

- monitoring and characterisation of combustion flames
- flow measurement of particulate solids
- medical instrumentation
- control of autonomous vehicles
- control of time-delay systems
- high-speed architectures for real-time image processing
- novel signal processing architectures based on logarithmic arithmetic.

Careers

The programme targets producing engineers with the knowledge and skills required for working in the communications industry on programmable hardware, in particular. There is a high demand for people to fill such roles in communications and test & measure equipment vendors, and in many smaller companies developing devices for the internet of things.

Kent has an excellent record for postgraduate employment: over 94% of our postgraduate students who graduated in 2013 found a job or further study opportunity within six months.

We have developed our programmes with a number of industrial organisations, which means that successful students are in a strong position to build a long-term career in this important discipline. You develop the skills and capabilities that employers are looking for, including problem solving, independent thought, report-writing, time management, leadership skills, team-working and good communication.

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

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This course considers current research and practice in cyber security. You will develop technical expertise and practical skills in the design, management and evaluation of secure systems, and in the use of tools and techniques for penetration testing and cyber defence. Read more
This course considers current research and practice in cyber security. You will develop technical expertise and practical skills in the design, management and evaluation of secure systems, and in the use of tools and techniques for penetration testing and cyber defence. This MSc can lead to a career such as a network system administrator, security analyst, ethical hacker or a security consultant.

Why choose this course?

The MSc Cyber Security consists of two major parts: taught modules and an MSc project. Each taught module has an assigned number of credits (either 15 or 30). In order to obtain an MSc degree you must study and pass 120 credits of compulsory taught modules plus the project i.e. 180 credits in total.

[[Careers
Our masters 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 for a career such as a software engineer, developer or project manager.

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 masters 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

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.

This offers 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

Core Modules
-Advanced Computer Science Masters Project
-Programming Paradigms

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

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