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Masters Degrees (Neural Networks)

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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 Neural Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.

On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.

See the website http://www.ru.nl/english/education/masters/neural-computing/

Why study Neural Computing 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.

- 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.

- 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.

-Computational framework for counterfactual predictive processing

In a recent paper we introduced a computational framework, based on causal Bayesian networks, to computationally flesh out the predictive processing processing framework in neuroscience. In this project we want to extend this to so-called counterfactually rich generative models in predictive processing. Such models encode sensorimotor contingencies, that is, they represent 'what-if' relations between actions and sensory inputs. We aim to further operationalize this account using Pearl's intervention and counterfactual semantics. In this project you will combine formal computational modelling with conceptual analysis. 

- 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 and technical expertise . 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 or joined recent startups.

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

Instead of an extended research project (45 ec) you can also choose to do a smaller (30 ec) research project plus a 15 ec internship, giving you plenty of hands-on experience with AI. We encourage students to do this internship abroad.



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About the course. Read more

About the course

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

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

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

Reasons to Study

• Internationally recognised reputation

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

• Benefit from our Research Expertise

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

• Flexible study options

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

• Dedicated robotics laboratory

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

• Employment Prospects

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

Course Structure

Modules

First semester

• Research Methods

• Artificial Intelligence Programming

• Mobile Robots

• Fuzzy Logic

Second semester

• Artificial Neural Networks

• Computational Intelligence Optimisation (CIO)

• Applied Computational Intelligence

• Data Mining, Techniques and Applications

(Intelligence Systems only)

• Intelligent Mobile Robots (Intelligent Systems

and Robotics only)

Third semester

• Individual Project

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

Teaching and Assessment

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

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

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

Contact and learning hours

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

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.

Academic expertise

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

To find out more

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

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

Applying for a postgraduate course:

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

Funding for postgraduate students

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



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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
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
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
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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This MSc programme will develop your knowledge and skills to an advanced level in key aspects of telecommunications and wireless systems. Read more
This MSc programme will develop your knowledge and skills to an advanced level in key aspects of telecommunications and wireless systems.

The course content is updated annually to maintain industry relevance and to reflect the latest developments in the industry.

This programme can be studied full or part time. The first two sections consist of lectures, laboratory classes and seminars, with a final section devoted to an individually supervised project.

You will study the following core (compulsory) topics during the MSc:

Wireless systems and designs
Communication networks and security
Research skills and management
Signal processing
Cellular radio communications systems related topics.
In addition you can choose from the following options to take account of your interests:

Optical fibre systems
Radio propagation and antennas
Communication signal processing
Neural networks
Integrated circuit design.
To meet the increasing demands for MSc students with industry experience, the Department of Electrical Engineering and Electronics has introduced a 2-year MSc programme for graduates of the highest calibre to develop advanced knowledge and skills in telecommunications and wireless systems and give students the opportunity to put their knowledge into practice through valuable work experience during a one year industrial placement.

Graduates will be capable of undertaking research and development work in telecom and wireless systems, and also developing and managing R&D programmes.

This 2-year MSc programme EETI shares the same taught modules with its equivalent 1-year MSc in telecommunications and wireless systems (EETW) in year 1. But unlike the 1-year MSc students who do their MSc project over the summer, students on the 2 year MSc (EETI) are required to undertake an industrial project and placement (either in the UK or overseas) in year 2, typically 30 weeks from September to next June.

This opportunity to work in industry will help students strengthen their career options by

Undertaking the project work in an industrial setting;
Applying theory learnt in the classroom to real-world practice;
Developing communications and interpersonal skills;
Building networks and knowledge which will be invaluable throughout their career.

The placement

During the placement year students will spend time working in a relevant company suitable for the MSc. This is an excellent opportunity to gain practical engineering experience which will boost students’ CV, build networks and develop confidence in a working environment. Many placement students continue their relationship with the placement provider by undertaking relevant projects and may ultimately return to work for the company when they graduate.

The University of Liverpool has a dedicated team to help students find a suitable placement. Preparation for the placement is provided by the University’s Careers and Employability Services (CES) who assist students in finding a placement, help students produce a professional CV and prepare students for placement interviews. Placements can be near or far in the UK or overseas.

The University has very good links with industry; companies (such as ARM Plc) have offered our MSc students competitive placements. Although industry placements are not guaranteed, the University offers students opportunities and support throughout the process to ensure that the chance for a student to find a placement is high.

If a student is unable to secure a suitable placement by the end of April during year 1, the student will be transferred onto the 1-year MSc to undertake the MSc project over the summer and graduate after one year.

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The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. Read more
The School of Engineering and Digital Arts offers research-led degrees in a wide range of research disciplines, related to Electronic, Control and Information Engineering, in a highly stimulating academic environment. The School enjoys an international reputation for its work and prides itself in allowing students the freedom to realise their maximum potential.

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.

We undertake 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.

We have research funding from the Research Councils UK, European research programmes, a number of industrial and commercial companies and government agencies including the Ministry of Defence. Our Electronic Systems Design Centre and Digital Media Hub provide training and consultancy for a wide range of companies. Many of our research projects are collaborative, and we have well-developed links with institutions worldwide.

Visit the website https://www.kent.ac.uk/courses/postgraduate/262/electronic-engineering

Project opportunities

Some projects available for postgraduate research degrees (http://www.eda.kent.ac.uk/postgraduate/projects_funding/pgr_projects.aspx).

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

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.

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.

Building on Kent’s success as the region’s leading institution for student employability, we offer many opportunities for you to gain worthwhile experience and develop the specific skills and aptitudes that employers value.

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

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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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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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Advances in technology are yielding smaller and higher-performance computer systems permeating into a wide range of applications, from communication systems to consumer products and common household appliances. Read more
Advances in technology are yielding smaller and higher-performance computer systems permeating into a wide range of applications, from communication systems to consumer products and common household appliances. Computer engineering encompasses the principles, methods, and modern tools for the design and implementation of computing systems.

Our MSc Computer Engineering is the first in the UK and provides a balanced perspective of both hardware and software elements of computing systems, and their relative design trade-offs and applications. It will build on your knowledge in mathematics, science, and engineering to ensure you have a sound foundation in the areas needed for a career in this field.

Laboratory experiences enable you to understand experimental design and simulation techniques. We are internationally leading in this and you will have access to unique computer engineering platforms including our:
-Intelligent Flat (iSpace)
-Robotics Arena
-Networked intelligent campus (iCampus)
-Advanced networking and multimedia labs

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.

Professional accreditation

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

Our expert staff

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

Upon graduation, you can look for employment in:
-Heavy industries, designing advanced computer systems and control
-Hardware companies, designing and developing microprocessors, personal computers, and supercomputers
-Communication and mobile phone companies, designing advanced computer systems for communications systems
-Large computer and microelectronics companies, writing software and firmware for embedded microcontrollers, and designing VLSI chips, analog sensors, mixed signal circuit boards, and operating systems
-Embedded system companies, developing advanced computer systems, and mobile applications and phones
-Banks and businesses, designing intelligent distributed systems to serve their operations
-Computer games companies, designing advanced computer games
-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) and within our University.

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

-MSc Project and Dissertation
-Converged Networks and Services
-Digital Signal Processing
-High Level Logic Design
-Professional Practice and Research Methodology
-Programming Embedded Systems
-Advanced Embedded Systems Design (optional)
-Artificial Neural Networks (optional)
-Constraint Satisfaction for Decision Making (optional)
-Creating and Growing a New Business Venture (optional)
-Electronic System Design & Integration (optional)
-Intelligent Systems and Robotics (optional)
-Mobile Communications (optional)

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The Master’s programme in. Computer Engineering. at Vistula University is your opportunity to gain expert knowledge and start a career in the IT sector. Read more

The Master’s programme in Computer Engineering at Vistula University is your opportunity to gain expert knowledge and start a career in the IT sector. If you choose this programme, you will discover the applications of advanced wireless technologies in organisations, and learn how to design mobile applications for various companies and their products. In addition, graduating with a Master’s degree will open the doors to managerial positions in the industry.

This programme is ideal for all STEM graduates, who would like to expand their knowledge of computer engineering, and gain new skills.

The Master’s programme will teach you optimisation and the R language. You will learn how to use the knowledge of algorithms, applicable to problems in wireless network and mobile device software design. You will gain new competencies related to profitability assessment and project management.Thanks to Microsoft’s DreamSpark, Oracle’s OAI and CISCO’s Local Academy education programmes, you will become adept at applying theoretical knowledge to real-world problems. As a Master of Computer Engineering, you will also boast the mastery of design and development tools.

REQUIREMENTS

If you want to apply for the Computer Engineering Master’s programme, you must be a holder of a BS diploma (in computer engineering or related fields, e.g. telecommunications or electronics). You will be asked to present this diploma. 

The Faculty of Engineering ( Institute of Computer Science ) organizes monthly cyclical meetings – Scientific Seminars, where there is an opportunity to hear and actively participating in cooperation of research in the field of computer science and its applications in some other fields.

Konwersatorium – spis – download

The 27th workshop on Concurrency, Specification, and Programming 2018 (CS&P’18) deals with formal specification of concurrent and parallel systems, mathematical models for describing such systems, and programming and verification concepts for their implementation.

From our Faculty of Engineering Prof. Ludwik Czaja, Prof. Dmitry Zaitsev, dr Soma Dutta, mgr Edip Senyurek are members of the Program Committee of the international conference CS&P’2018 (in Berlin)

Topics of the workshop include, but are not limited to:

  • Mathematical models of concurrency
  • Formal specification languages
  • Theory of programming
  • Model checking and testing
  • Multi-agent systems
  • Rough sets
  • Verification
  • Formal aspects of knowledge management
  • Knowledge discovery and data mining
  • Soft computing
  • Applications, e.g. in Robotics

Programme

ABOUT PROGRAMME

The Master’s programme in Computer Engineering will significantly expand the knowledge you have gained in the Bachelor’s programme. The programme will teach you how to design wireless networks and mobile applications. You will acquire the skills that will enable you to manage projects, and lead your own IT teams. See the entire curriculum, and find out how much more you can learn!

INTERSHIP

Vistula University offers practical knowledge, shared by experts and reputable specialists. We believe that experience and the ability to utilise theoretical knowledge is the key to success. This is why the computer engineering programme (Master’s level) includes internships. These will help you solidify your knowledge, and become a confident specialist. Furthermore, you will also have the valuable opportunity to network.

EXPERTISE

Studying at Vistula University will provide you with the knowledge necessary, to quickly become an expert in computer engineering.

  • List of obligatory classes
  • Advanced statistical calculations in R
  • Software engineering design templates
  • ICT networks
  • Select applications of discrete optimisation
  • Wireless and mobile systems safety
  • Neural networks and deep learning in machine learning
  • Introduction to enterprise and project management
  • Humanities course: Professional ethics in business
  • MA seminar
  • Physical education
  • Foreign languages


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

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

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

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

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

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

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

Professional accreditation

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

Our expert staff

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

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

Specialist facilities

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

Your future

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

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

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

Example structure

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

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Course formats. All of our taught MSc courses are available in several formats. - 12-month intensive MSc for graduates with a good Honours degree. Read more
Course formats

All of our taught MSc courses are available in several formats:

- 12-month intensive MSc for graduates with a good Honours degree
- 2-year International Masters for overseas students with an ordinary Bachelors degree
- With an optional industrial placement (8-50 weeks of paid work experience)
- Part-time over 3 years

Course overview

This conversion course prepares graduates from any discipline for a career in, or involving, computing. No prior knowledge of computer science is required. A broad introduction is provided, including the key technologies and skills needed for employment. You can explore your personal interests through a variety of optional modules. Advanced intellectual, teamwork, communication and other transferable skills are developed.

Hundreds of past graduates from this course are now working across the globe for companies such as IBM, Cisco, Logica/CMG, Pfizer, Reuters, Shell and Zurich Financial. Some chose technical careers in leading software houses, advanced technology companies or commercial sectors. Others work at the interface between technicians and clients, as systems analysts or consultants. Many now hold senior positions as project leaders or managers. You might like to follow in their footsteps.

Funding is available for well-qualified students of any nationality.

Further details: http://www.cs.kent.ac.uk/teaching/pg/

Course content (Honours degree entry; see above web page for details of Ordinary degree entry)

If you have not studied programming before, or only a little (introductory stream)

- Introduction to Object-Oriented Programming (Java)
- Advanced Object-Oriented Programming (Java)

If you have a good working knowledge of programming (advanced stream)

- Advanced Java for Programmers

Other core modules for all students:

- Software Engineering
- Web-based Information System Development
- Systems Architecture
- Logic and Logic Programming
- Project Research
- Project and Dissertation

Optional modules available to all students (choose 1):

- Advanced English for Academic Study
- Computer Graphics and Animation
- Contracts, Professional Responsibility and Computing Law
- Data Mining and Knowledge Discovery
- Introduction to Intelligent Systems
- Mobile and Ubiquitous Computing

Additional options for advanced stream only (choose 1 more):

- C++ Programming
- Cognitive Neural Networks
- Human-Computer Interaction
- IT Consultancy Methods
- IT Consultancy Practice (includes work experience)
- Networks and Network Security

Optional industrial placement (8-50 weeks of paid work experience).

The options available may vary from year to year and are subject to timetabling and prerequisite constraints.
Advanced English for Academic Study may be compulsory for non-native speakers who need additional support.

Further details: http://www.cs.kent.ac.uk/teaching/pg/

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