Masters Degrees (Cognitive Computing)

Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Research Methods in Psychology and Cognitive Neuroscience at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).

This Master's degree in Research Methods in Psychology and Cognitive Neuroscience aims to equip students with the skills necessary for research careers across a range of scientific areas.

Key Features of Research Methods in Psychology and Cognitive Neuroscience

Performance:

- One of four Psychology departments to achieve a 100% 4* rating (maximum score possible) for the reach and significance of its work in the Research Excellence Framework (REF) 2014. Based on this measure Psychology at Swansea was ranked 14th (out of 82) in the UK

- Top third ranking for UK Psychology Departments (2016 Complete University Guide)

- Joint 12th UK ranking for Psychology (Graduate prospects)

- The MSc Research Methods in Psychology and Cognitive Neuroscience is unique and novel in the range of modules and techniques the programme offers

Teaching and Employability:

- Teaching is carried out by highly-respected, research active, professionals conducting research across a range of cognitive neuroscience research areas and publishing in top international journals

- Students benefit from state-of-the-art technology with over twenty general purpose research rooms and numerous specialised testing facilities

- Ability to offer international students mentoring throughout the course

Research Methods in Psychology and Cognitive Neuroscience is at the intersection of cognitive science, brain imaging, and clinical neuroscience.

It is considered one of the most significant areas of contemporary science and it is beginning to transform the understanding of both normal and damaged brain function.

The importance of cognitive neuroscience has been recognised by the Welsh Government which created the multi-centre Wales Institute of Cognitive Neuroscience, drawing together the psychology departments at Swansea, Cardiff and Bangor Universities.

A core aspect of the provision for MSc Research Methods in Psychology and Cognitive Neuroscience will also be collaboration with the College of Medicine at Swansea University.

Modules

Modules on the Research Methods in Psychology and Cognitive Neuroscience may include:

Theoretical Issues in Cognitive Neuroscience

Practical Applications in Cognitive Neuroscience

Statistical Methods

Computing skills

Generic Research Skills

Special Research Skills

Neuropsychology

Introduction to Research Programming

Psychology of Ageing

Research Methods in Psychology and Cognitive Neuroscience Course Structure

The full-time master's degree for Research Methods in Psychology and Cognitive Neuroscience is studied over one year and involves attending University for two full days a week (Monday and Tuesday).

The part-time degree in Research Methods in Psychology and Cognitive Neuroscience, which is studied over two years, normally involves attending the University for one full day a week.

Taught modules are provided in the first two semesters, with a final high credit-bearing empirical research project with a strong cognitive neuroscience component typically undertaken over the summer.

Sessions may be arranged occasionally on other days of the week (e.g. visiting clinician talks/workshops and employability sessions).

Who should apply?

The Research Methods in Psychology and Cognitive Neuroscience course is suitable for:

- anyone looking for a valuable academic foundation for future doctoral training

- anyone looking to demonstrate their employability across a range of disciplines within cognitive neuroscience and related fields, including psychology, computing, neuroscience, medicine and computer science

- UK and international psychology graduates seeking positions as researchers in psychology, cognitive neuroscience or related fields.

- psychology graduates aiming to secure a PhD by research in a psychology, cognitive neuroscience, or a related discipline

- graduates from other disciplines such as Biology, Neuroscience, and Medicine who wish to develop further skills related to psychology and cognitive neuroscience

Career Prospects

Students have successfully used the Research Methods in Psychology and Cognitive Neuroscience qualification to gain positions on PhD research programmes. Others have successfully gained employment as Research Associates/ Officers, as well as working in Teaching positions, the Business Sector and in Administration.

On completion of the Research Methods in Psychology and Cognitive Neuroscience course students should also be able to demonstrate their employability across a range of disciplines within cognitive neuroscience and related fields, including psychology, computing, neuroscience, medicine and computer science.

Staff Expertise

Many of the College of Human and Health Sciences team are leaders in their specialist fields of research. They undertake novel and original research in a variety of areas, including clinical and health psychology, brain injury, sleep, cognition, neuroscience and developmental psychology.

Postgraduate Community

The College of Human and Health Sciences has a vibrant postgraduate community with students drawn from a variety of backgrounds and nationalities. The College is known for its friendly, welcoming and supportive environment, which combined with its extensive facilities, state-of-the-art technology and superb beachside location, helps to ensure that students benefit from an exceptional student experience.

In addition, students have access to a wide range of excellent facilities and equipment for realistic workplace experiences.

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Learn how different brain functions contribute to cognition, mediate social interaction, and determine mental health, well-being and psychiatric illness.

Who is it for?

This Masters is ideal for those who have an undergraduate degree in Psychology or a related discipline and would like to build more knowledge and skills highly valued both in academic research and the clinical professions. The MSc is an ideal platform from which to progress to PhD studies, particularly in Cognitive or Social Neuroscience. Students will also be well-equipped should they wish to undertake further professional training in Clinical Psychology, or a related discipline.

Objectives

This Masters degree bridges three research and clinical disciplines:
-Cognitive neuroscience (the study of human brain functions such as memory, perception and language).
-Clinical neuroscience (the understanding of neurological, psychological or psychiatric illness via their neural and cognitive antecedents).
-Social neuroscience (the investigation of brain processes that help us communicate, feel, learn and interact with others).

The major aim of this programme is to provide you with a thorough grounding in the neuroscience that underpins human cognitive brain function, clinical, social and affective interaction, and neuropathology.

Teaching will comprise of seminars, lectures, computing and statistics classes, and supervision of an individual research project. Your learning experience during the programme will be enhanced by an invited speaker’s programme of external experts who work in clinical, social or cognitive neuroscience.

Academic facilities

You will have access to all the facilities and laboratories in the Psychology Department. Our members have experience with a wide range of neuroscientific techniques, including neuropsychological testing, psychophysics and functional Magnetic Resonance Imaging (fMRI).

We have particular strengths in the use of Electroencephalography (EEG), Transcranial magnetic stimulation (TMS) and Transcranial Electric Stimulation (a weak current applied to the scalp), in addition to measures of human behaviour (e.g. response times, response errors, and eye movements) and physiological measures (e.g. galvanic skin response and heart rate).

We test neurologically normal individuals, special populations (e.g. people with synesthesia) and people with expertise or acquired skills (e.g. dancers, musicians, athletes), as well as people with brain damage (e.g. neglect or split-brain patients), psychiatric diagnoses (e.g. schizophrenia), sensory deficits (e.g. visual and hearing impairments) and developmental disorders (e.g. dyslexia or autism).

Placements

We help facilitate Clinical placements and are able and offer Research placements within our department.

Clinical placements: Center for Psychological Wellbeing and Neuroscience (CPWN) in collaboration with City and Hackney Mind (CHM).

Teaching and learning

Teaching will be comprised of lectures, seminars, group work and discussions, workshops and tutorials, reports, computing and statistics classes and the individual research dissertation.

You will undertake independent study, supported by the teaching and learning team, and will receive detailed feedback on your coursework. You will be provided with assessment and grade-related criteria which will outline your intended learning outcomes, along with the skills, knowledge and attitudes you are expected to demonstrate in order for you to complete an assessment successfully. You will also be assigned a personal tutor as your primary contact, who will advise you on academic matters and monitor your progress through the programme.

You will find a supportive vibrant research environment in the Department. The course is taught by academics, who are internationally recognised experts in their field with different backgrounds in clinical, social and cognitive neuroscience.

Assessment

Your learning will be assessed through essays, examinations, oral presentations, research methods projects and interpretation of statistical analyses, formal research proposals and a dissertation.

Modules

The programme consists of eight taught modules worth 15 credits each with around 30-34 hours of face-to-face contact, supported by online resources and an empirical research project (worth 60 credits).

You will learn about the latest advances in clinical, social and cognitive neuroscience and develop an appreciation of the reciprocal nature of research and practice in these domains. For example how insights from functional neuroimaging inform our understanding of neurological disorders and how clinical observations inform neurocognitive modelling.

Course structure
-Principles of Neuroscience: Brain anatomy, techniques and paradigms
-Developmental Cognitive Neuroscience
-Mental Health, Well-being and Neuroscience
-Fundamental Processes in Cognitive Neuroscience & Neuropsychology I
-Fundamental Processes in Cognitive Neuroscience & Neuropsychology II
-Social Cognition and the Social Brain
-Statistical models and Research Methods and Programming
-Research Dissertation
-Invited speakers programme

Career prospects

This course will provide you with knowledge and skills highly valued both in academic research and the clinical professions. The MSc is an ideal platform from which to progress to PhD studies, particularly in Cognitive or Social Neuroscience. You will also be well-equipped should you wish to undertake further professional training in Clinical Psychology, or a related discipline.

The knowledge and skills you will acquire in this programme are highly valuable, whether you choose to pursue further research or an applied occupation. They will enhance your employability prospects in a wide range of sectors including the pharmaceutical industry, neuromarketing, the computing industry, science and the media, science and the arts, business or education.

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

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

This has enabled us to understand their needs for Data Scientists, what skills will be required and on successful completion of this course individuals will be highly employable within businesses.

Having this close understanding of what industry needs makes this course relatively unique and the very best suited to these looking for a career in the Data Sciences.

The course will be of specific interest to :

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

Data Science Foundation
Managing Data
Data Exploration and Analysis
Mathematics
Machine Learning & Cognitive Computing
Data Visualisation and Presentation
The 1 year full time MSc course will be stimulating and interactive, making use of lectures, self-learning, workshops and hands-on projects.

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

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

We believe Data Science is very much an intellectual ‘contact sport’ and through this course we provide you with every opportunity to put your theoretical knowledge into practice.

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

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

Fees for 2017

Home fees - 1 year full-time: £8000.00

International fees: £10,920.00

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

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

You will have access to the very best IT facilities in order to support your studies. These range from computer labs to access to cloud analytics from the leading providers.

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

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

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

Where this can take you
The course has been designed to provide you with a very practical understanding of the issues associated with sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations.

On completion of your MSc studies and successful graduation, you will have very transferable skills and can choose to move directly in to the workplace perhaps in retail, banking, government or transport.

Indicative modules
Data Science Foundation (20 Credits)
Managing Data (20 Credits)
Data Exploration and Analysis (20 Credits)
Mathematics (20 Credits)
Machine Learning & Cognitive Computing (20 Credits)
Data Visualisation and Presentation (20 Credits)
Dissertation/Project (60 Credits)


Teaching and Assessment
Our approach to supporting your learning, and how your learning is assessed, is designed to mirror the workplace environment. With this in mind, key features of our approach to learning and assessment include the following:

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

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Understanding the relationship between brain, cognition and behaviour is one of the main challenges the scientific community is currently facing. Which neural processes underlie “free” decisions, the formation of new memories, the emergence of conscious experience? Computational cognitive neuroscience is a young and exciting discipline that tackles these long-standing research questions by integrating computer modelling with experimental research.

This Masters programme will foster a new generation of scientists who will be trained in both neurocomputational modelling as well as cognitive neuroscience. Its core topics include theory and practice of biologically constrained models of neurons, cortical circuits, and higher cognitive functions (memory, decision making, language), and fundamentals of cognitive neuroscience (brain mechanisms and structures underlying cognition and behaviour, as well as modern neuroimaging and data analysis techniques). The programme is suitable for students from a variety of disciplines (including psychology, computing, neuroscience, engineering, biology, maths, physics, or related subjects), and students with no prior programming experience are welcome. Thanks to the highly multidisciplinary and cutting-edge nature of the programme, graduates of this Masters will acquire a unique set of complementary skills that will make them extremely competitive in securing research or analyst positions in both academia and industry.

You will study the following modules:

 

TERM 1

1. Foundations of Neuroscience (PS74005D), which covers brain anatomy and functions and modern experimental techniques to study the neural basis of behaviour.
2. Statistical Methods (PS71020D). This module covers primary statistical analyses used in psychology and neuroscience (including multivariate data screening and cleaning; power and sample size determination; factor analysis; multiple regression; analysing contrasts; univariate and multivariate repeated measures; ANCOVA; MANOVA and psychometrics).
3. A choice between Data Programming (IS71068A) or a new PG MATLAB module which is due to be offered by Psychology in 2018 .

Term 2

1. A new module called “Cortical Modelling”: this will cover theory and practice of computational neuroscience (including computational models of neurons, synapses, simple cortical circuits and networks). Students will learn how to implement simple models of biologically-realistic neural systems.
2. A new module called “Cognitive Neuroscience”, which will cover the current state of knowledge in the field of cognitive neuroscience. It covers lower-level, fundamental cognitive processes, such as perception, attention, action, vision, audition, and motor control, as well as higher functions such as memory, speech, language, executive functions and cognitive control.
3. A new module called “Modelling cognitive and higher brain functions” : fundamental principles of current computational models of human cognitive and brain functions and their emergence (including vision, attention, memory, decision making, and language)
4. Advanced Quantitative Methods (PS71082A): Theory and practice in the application of advanced quantitative methods across multiple areas of psychology and neuroscience.

TERM 3

   1. Research Project which will be carried out by combining the computational, experimental and data analysis skills that students will acquire over Term 1 and 2.

OPTIONAL MODULES:

In Term 1, students will have to choose one amongst the following 4 options (each 15 CATS, level 7):

- Neural Networks (IS57002A)

- Machine Learning (IS71071A)

- Natural Computing (IS71072A)

- Data and Machine Learning for Artistic Practice (IS71074A)

 

Please note that the new modules may change subject to approval

Please note that due to staff research commitments not all of these modules may be available every year.

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Research programme

The academic staff in the Applied Computing Department (ACD) are all engaged in research and publications. Considering its modest size, ACD has successfully attracted research funding from various sources in the UK and the EU, including industry, research councils, HEA and EU framework projects such as FP6. Furthermore, ACD has been working and collaborating with many European research institutions.

For the academic year 2012-2013, 2 DPhil and 6 MSc students (1 in Mathematics) have graduated, four of whom graduated with Distinction. The 2 DPhil students have made it for the March graduation and we expect to have 3 or 4 more completing their DPhil research programmes for the next graduation. One of our new MPhil/DPhil students in Computing joined the Department last October, and 3 other MPhil/DPhil students have joined us since. Over the last few years, the number of research students in ACD has grown steadily to (currently) 29 PhD and 2 Master’s research students.

We have had over 20 refereed conference and journal papers published during the last 12 months, and two of the papers have been awarded best paper awards.

ACD supports diverse research topics addressing varied applied computing technologies such as:

- Image processing and pattern recognition with applications in biometric-based person identification, image super-resolution, digital watermarking and steganography, content-based image / video indexing and retrieval, biomedical image analysis.
- Multi-factor authentication and security algorithms.
- Wireless networks technologies (Multi-frequency Software-Defined / Cognitive Radios, convergence and integration of different wireless technologies and standards such as WiFi and WiMax, IPv4 and IPv6, wireless mesh technologies, intrusion detection and prevention, efficiency and stability of ad hoc networks).
- Hybrid navigation and localisation integrations for mobile handsets, including using Cellular and WiFi in conjunction with GPS and Glonass for seamless positioning indoors, Multiplexed receive chain of GPS/Glonass with on-board handset Bluetooth/WiFi, GNSS signals multiplexing for real time simulation.
- Cloud computing, including the readiness of mobile operating systems for cloud services and focusing on techniques for fast computing handovers, efficient virtualisation and optimised security algorithms.
- Data mining techniques, including database systems, the application of data mining techniques in image and biological data, human-computer interaction and visual languages.
- Research and development of Apps for mobile devices and smart TVs, particularly for application in the areas of education and healthcare.
- Differential geometry – Einstein metrics, quasi-Einstein metrics, Ricci solitons, numerical methods in differential geometry.

As well as researching the chosen subject, our students engage in delivering seminars weekly, attending conferences and workshops, attending online webinars and discussion forums, attending training and focused group studies, supervising tutorial and laboratory sessions for undergraduate students, peer reviews and final year project supervision, among a host of technical and networking activities to enhance their skills and techniques.

Find out more about our Department of Applied Computing on http://www.buckingham.ac.uk/appliedcomputing.
Apply here http://www.buckingham.ac.uk/sciences/msc/computingresearch.

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

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

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

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

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

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

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

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This highly practical course will appeal to computing graduates seeking careers as professional software engineers and equip them with the skills necessary to succeed.

Employers often complain that computing graduates lack real-world practical skills. The Advanced Software Development MSc addresses software development for new and emerging platforms such as mobile phones/pads, multi-core processors and cloud computing. Modern development environments, languages and tools are also covered.

All taught Master’s programmes at the School of Computing are available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/251/advanced-software-development

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.

This programme is available with an optional industrial placement.

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.

CO838 - Internet of Things and Mobile Devices (15 credits)
CO846 - Cloud Computing (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO880 - Project and Dissertation (60 credits)
CO885 - Project Research (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO894 - Development Frameworks (15 credits)
CO889 - C++ Programming (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO641 - Computer Graphics and Animation (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO847 - Green Computing (15 credits)
CO899 - System Security (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, 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 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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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/

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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. 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/

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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.

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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Over the last decades, improvements in technology have led to a rapid increase in the use of neuroimaging to study human brain function non-invasively in health and disease. In particular, functional magnetic resonance imaging (fMRI), electro-encephalography (EEG), magneto-encephalography (MEG) and transcranial magnetic stimulation (TMS) are now routinely used by neuroscientists to study brain-behaviour relationships. Our MSc in Brain Imaging showcases Nottingham’s multi-disciplinary environment and offers a comprehensive programme that will provide you with the theoretical knowledge and practical skills required to conduct high-quality neuroimaging work and neuroscience research. Translational in vivo neuroscience approaches in animal models will also be considered, and interested students will have the opportunity to receive research training in this area.

The MSc in Brain Imaging has a flexible course structure and offers four pathways with core modules alongside a choice of optional modules that permits tailor-made study. The options are:

MSc Brain Imaging (Cognitive Neuroscience)
MSc Brain Imaging (Neuropsychology)
MSc Brain Imaging (Integrative Neuroscience)
MSc Brain Imaging (Developmental Science)

Graduating from the University of Nottingham opens up a wide range of career options. Many of our students use this programme as a preparation for PhD study or other advanced degree positions. Others opt for science-related jobs. Our graduates are highly regarded by employers in private and public sector organisations because of the solid academic foundation and transferable skills they gain during their degree course such as analytical evaluation, data management, statistical analysis as well as presentation and writing skills. In the past, graduates of this programme have taken-up career opportunities in university, hospital and industry settings.

Please email [email protected] for more information or visit the PG prospectus. Given the breadth of training available, the MSc is recommended to students with a background in psychology, neuroscience or a bioscience discipline as well as those with training in physics, engineering, mathematics, or computer sciences.

Upcoming Open Days: Wednesday 29 June and Wednesday 6 July (1.30-3 pm). Please contact us if you have specific questions about the programme. Phone: +44 (0)115 951 5361 or email: [email protected]

Key facts

• Programme delivered through lectures, practicals and research project resulting in a dissertation
• Core and optional modules according to specific pathways
• Four pathways with applications in Cognitive Neuroscience, Developmental Science, Neuropsychology, and Integrative Neuroscience
• Taught by active and internationally renowned research scientists
• Interdisciplinary approach with specialist lectures and/or project supervision by scientists from: the School of Psychology; Sir Peter Mansfield Magnetic Resonance Centre; Department of Academic Radiology

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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.
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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This programme aims to prepare students for a successful career in the IT sector, even if they do not have a prior degree in computer science. It enables students who have studied computer science previously to expand their knowledge and acquire further skills across a broader range of computer science topics.

Taught modules address mobile and cloud computing, big data and database systems, and the importance of information security, in relation to the foundational information systems principles.

This programme will equip you with professional skills that will allow you to work as an IT consultant/manager, system architect/analyst, or software developer in any industry field that heavily relies on software and information technology.

Programme structure

This programme is studied full-time over one academic year and part-time over three academic years. It consists of eight taught modules and a dissertation.

Example module listing

The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.

• Dissertation
• Information Systems Development
• HTML5 and CSS3 for Mobile Applications 
• Information Security Management 
• Information and Network Security 
• Practical Business Analytics 
• Database Systems 
• Project Management and Business Strategy
• Cloud Computing 
• Information Security for Business and Government

Educational aims of the programme

The aims of the programme are to:

• Prepare students for a range of computing related careers
• Enable students to understand, design and apply information systems and software development technologies
• Enable students to develop interest and basic skills for doing research in computer science
• Enable students to realise their full potential for learning and communication
• Enable students to appreciate rapid innovation and creativity in computer science

Programme learning outcomes

The programme provides opportunities for students to develop and demonstrate knowledge and understanding, skills, qualities and other attributes in the following areas:

Knowledge and understanding

Students will gain an understanding of:

• The principles of information systems and software development
• The principles and applications of contents technologies
• The practice of information systems and software development
• The professional issues involved in the exploitation of computing
• The areas of emergent and innovative computing technologies
• The key research issues in information and software systems

Intellectual / cognitive skills

Students will be able to:

• Understand and articulate the requirements of the users of software systems / applications
• Succinctly present, to a range of audience, knowledge relevant to the building, testing and deployment of a system
• Research and develop solutions through the application of systems analysis / software engineering methods

Professional practical skills

Students will gain the ability to:

• Specify, design and develop software systems and applications
• Critically evaluate software systems and tools
• Work as a member of a development team
• Communicate with potential and actual users and to understand their needs
• Retrieve Information
• Analyse data and present information in appropriate ways
• Plan, research, manage and implement a major project

Key / transferable skills

Students will gain skills in:

• Research and information retrieval skills
• Numeracy in both understanding and presenting cases involving a quantitative dimension
• Time management and organisational skills
• Self-learning skills
• Effective use of specialist IT facilities
• Continuing professional development

Global opportunities

We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.

In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.

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Taught by expert researchers, this innovative MSc combines evolutionary anthropology, focusing on the behaviour of human and non-human primates, with evolutionary, developmental and cognitive psychology.

You gain an interdisciplinary understanding of the origins and functions of human behaviour and can select from a range of advanced topics such as evolutionary anthropology, primatology, human behaviour, cognitive psychology, developmental psychology and intergroup relationships.

The programme places a strong emphasis on critical thinking and understanding of both the broad fields and the specialisms within. Core to the programme is the development of research methods, culminating in a piece of original research, written up in the form of a publication-ready journal article. The MSc in Evolution and Human Behaviour is a perfect foundation for PhD research: it provides theoretical background, discipline specific knowledge and advanced, quantitative research methods.

Visit the website https://www.kent.ac.uk/courses/postgraduate/190/evolution-and-human-behaviour

Why study with us?

- A unique, interdisciplinary, combination of Evolutionary Anthropology and Psychology.

- Taught by expert, active researchers in evolutionary approaches to understanding behaviour.

- Select from a range of advanced topics such as Evolutionary Anthropology, Primatology, Human Behaviour, Developmental Psychology & Cognitive Neuroscience.

- Perfect foundation for future PhD research: theoretical background, discipline-specific knowledge and advanced research methods.

- For students with an undergraduate degree in anthropology, psychology, biology or a related discipline.

- A research component that results in a publication-ready journal article.

Course structure

The programme places a strong emphasis on critical thinking and understanding of both the broad field and the specialisms within. Core to the programme is the development of research methods, culminating in a piece of original research, written up in the form of a publication ready journal article.

Modules

Please note that modules are subject to change. Please contact the School for more detailed information on availability.

SE992 - Advanced Topics in Evolutionary Anthropology (15 credits)
SP801 - Statistics and Methodology (40 credits)
SE993 - Advanced Topics in Primate Behaviour (15 credits)
SE994 - Advanced Topics in HUman Behaviour (15 credits)
SP844 - Advanced Topics in Group Processes (20 credits)
SP851 - Advanced Topics in Cognitive Development (20 credits)
SP856 - Groups and Teams in Organisations (15 credits)
SP827 - Current Issues in Cognitive Psychology and Neuropsychology (40 credits)
SP842 - Advanced Developmental Social Psychology (20 credits)
SE855 - Research Project (Evolution & Human Behaviour) (60 credits)

Assessment

Assessment is by computing tests, unseen examinations, coursework and a project report.

Programme aims

This programme aims to:

- provide the opportunity for advanced study of human behaviour from an evolutionary perspective, combining approaches from both evolutionary anthropology and evolutionary psychology

- provide teaching that is informed by current research and scholarship and that requires you to engage with aspects of work at the frontiers of knowledge

- help you to develop research skills and transferable skills in preparation for entering academic or other careers as an evolutionary scientist

- enable you to manage your own learning and to carry out independent research

- help you develop general critical, analytic and problem-solving skills that can be applied in a wide range of settings.

Careers

As a School recognised for its excellence in research we are one of the partners in the South East Doctoral Training Centre, which is recognised by the Economic and Social Research Council (ESRC). This relationship ensures that successful completion of our courses is sufficient preparation for research in the various fields of social anthropology. Many of our students go on to do PhD research. Others use their Master’s qualification in employment ranging from research in government departments to teaching to consultancy work overseas.

Higher degrees in anthropology create opportunities in many employment sectors including academia, the civil service and non-governmental organisations through work in areas such as human rights, journalism, documentary film making, environmental conservation and international finance. An anthropology degree also develops interpersonal and intercultural skills, which make our graduates highly desirable in any profession that involves working with people from diverse backgrounds and cultures.

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

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Learning how to turn real-world data sets into tools and useful insights, with the help of software and algorithms.

Data plays a role in almost every scientific discipline, business industry or social organisation. Medical scientists sequence human genomes, astronomers generate terabytes of data per hour with huge telescopes and the police employ seismology-like data models that predict where crimes will occur. And of course, businesses like Google and Amazon are shifting user preference data to fulfil desires we don’t even know we have. There is therefore an urgent need for data scientists in whole array of fields. In the Master’s specialisation in Data Science you’ll learn how to turn data into knowledge with the help of computers and how to translate that knowledge into solutions.

Although this Master’s is an excellent stepping-stone for students with ambitions in research, most of our graduates work as data consultants and data analysts for commercial companies and governmental organisations.

Why study Data Science at Radboud University?

- This specialisation builds on the strong international reputation of the Institute for Computing and Information Sciences (iCIS) in areas such as machine learning, probabilistic modelling, and information retrieval.
- We’re leading in research on legal and privacy aspects of data science and on the impact of data science on society and policy.
- Our approach is pragmatic as well as theoretical. As an academic, we don’t just expect you to understand and make use of the appropriate tools, but also to program and develop your own.
- Because of its relevance to all kinds of different disciplines, we offer our students the chance to take related courses at other departments like at language studies (information retrieval and natural language processing), artificial intelligence (machine learning for cognitive neuroscience), chemistry (pattern recognition and chemometrics) and biophysics (machine learning and optimal control).
- The job opportunities are excellent: some of our students get offered jobs before they’ve even graduated and almost all of our graduates have positions within six months after graduating.
- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Computing Science together with the specialisation in Web and Language Interaction (Artificial Intelligence). This will take three instead of two years.

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

Admission requirements for international students

- A proficiency in English
In order to take part in the programme, you need to have fluency in English, both written and spoken. Non-native speakers of English without a Dutch Bachelor's degree or VWO diploma need one of the following:
- TOEFL score of >550 (paper based) or >213 (computer based) or >80 (internet based)
- IELTS score of >6.0
- Cambridge Certificate of Advanced English (CAE) or Certificate of Proficiency in English (CPE), with a mark of C or higher

Career prospects

A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data:
- To come up with a creative and useful solution.
- To find or program the right tool to turn the data into knowledge.
- To communicate the obtained findings to others.

By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

The job perspective for our graduates is excellent. Industry desperately needs data science specialists at an academic level, and thus our graduates have no difficulty in find an interesting and challenging job. A few of our graduates decide to go for a PhD and stay at the university, but most of our students go for a career in industry. They then typically either find a job at a larger company as consultant or data analysis, or start up their own company in data analytics.

Examples of companies where our graduates end up include SMEs like Orikami, Media11 and FlexOne, and multinationals like ING Bank, Philips, ASML, Capgemini, Booking.com and perhaps even Google.

Our approach to this field

Data nowadays plays a role in almost every scientific discipline as well as industry and is rapidly becoming a key driver of scientific discoveries, business innovation, and solutions for societal challenges such as better healthcare. Medical scientists are sequencing and analysing human genomes to uncover clues to infections, cancer, and other diseases. With huge telescopes, astronomers generate terabytes of data per hour to study the formation of galaxies and the evolution of quasars. Businesses like Google and Amazon are sifting social networking and user preference data to fulfill desires we don't even know we have. Police employing seismology-like data models can predict where crimes will occur and prevent them from happening.

It is then with good reason that data science has been called the sexiest job of the 21st century. Many companies complain about the difficulty to find skilled data scientists and predict this to be even harder in the future. A professional data scientist has fine problem-solving, analytical, programming, and communication skills. He or she applies those skills to analyse a problem in the light of the available real-world data, to come up with a creative and useful solution, to find or program the right tool to turn the data into knowledge, and to communicate the obtained findings to others. By combining data, computing power and human intellect, data scientists can make a real difference to help and improve our society.

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

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