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Masters Degrees (Cyber-Physical Systems)

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The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. Read more
The accredited Master of Science program in Computer Science is a two-year program that has been designed for international and German graduate students. The curriculum is very flexible. Students can compile their individual study plans based on their background and interests. It is also a very practical program. In addition to lectures and tutorials, students will complete two seminars, one or two projects and the master thesis.

In the beginning students will choose one or two key courses. Key courses are courses which introduce the students to the research areas represented at the Department of Computer Science. The following key courses are offered:

• Algorithm Theory
• Pattern Recognition
• Databases and Information Systems
• Software Engineering
• Artificial Intelligence
• Computer Architecture

After that, students can specialize in one of the following three areas:

• Cyber-Physical Systems
• Information Systems
• Cognitive Technical Systems

Here are some examples of subjects offered in the three specialization areas:

Cyber-Physical Systems:

• Cyber-Physical Systems – Discrete Models
• Cyber-Physical Systems – Hybrid Control
• Real Time Operation Systems and Reliability
• Verification of Embedded Systems
• Test and Reliability
• Decision Procedures
• Software Design, Modeling and Analysis in UML
• Formal Methods for Java
• Concurrency: Theory and Practice
• Compiler Construction
• Distributed Systems
• Constraint Satisfaction Problems
• Modal Logic
• Peer-to-Peer Networks
• Program Analysis
• Model Driven Engineering

Information Systems:

• Information Retrieval Data Models and Query Languages
• Peer-to-Peer Networks
• Distributed Storage
• Software Design, Modeling and Analysis in UML
• Security in Large-Scale Distributed Enterprises
• Machine Learning
• Efficient Route Planning
• Bioinformatics I
• Bioinformatics II
• Game Theory
• Knowledge Representation
• Distributed Systems

Cognitive Technical Systems:

• Computer Vision I
• Computer Vision II
• Statistical Pattern Recognition
• Mobile Robotics II
• Simulation in Computer Graphics
• Advanced Computer Graphics
• AI Planning
• Game Theory
• Knowledge Representation
• Constraint Satisfaction Problems
• Modal Logic
• Reinforcement Learning
• Machine Learning
• Mobile Robotics I

We believe that it is important for computer science students to get a basic knowledge in a field in which they might work after graduation. Therefore, our students have the opportunity to complete several courses and/or a project in one of the following application areas:

• Bioinformatics
• Educational Sciences
• Geosciences
• Cognitive Sciences
• Mathematics
• Medicine
• Meteorology
• Microsystems Engineering
• Physics
• Political Sciences
• Psychology
• Sociology
• Economics

In the last semester, students work on their master’s thesis. They are expected to tackle an actual research question in close cooperation with a professor and his/her staff.

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Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Read more
Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Your research will be supported by an experienced computer scientist within a research group and with the support of a team of advisers.

Research supervision is available under our six research areas, reflecting our strengths, capabilities and critical mass.

Advanced Model-Based Engineering and Reasoning (AMBER)

The AMBER group aims to equip systems and software engineering practitioners with effective methods and tools for developing the most demanding computer systems. We do this by means of models with well-founded semantics. Such model-based engineering can help to detect optimal, or defective, designs long before commitment is made to implementations on real hardware.

Digital Interaction Group (DIG)

The Digital Interaction Group (DIG) is the leading academic research centre for human-computer interaction (HCI) and ubiquitous computing (Ubicomp) research outside of the USA. The group conducts research across a wide range of fundamental topics in HCI and Ubicomp, including:
-Interaction design methods, eg experience-centred and participatory design methods
-Interaction techniques and technologies
-Mobile and social computing
-Wearable computing
-Media computing
-Context-aware interaction
-Computational behaviour analysis

Applied research is conducted in partnership with the DIG’s many collaborators in domains including technology-enhanced learning, digital health, creative industries and sustainability. The group also hosts Newcastle University's cross-disciplinary EPSRC Centre for Doctoral Training in Digital Civics, which focusses on the use of digital technologies for innovation and delivery of community driven services. Each year the Centre awards 11 fully-funded four-year doctoral training studentships to Home/EU students.

Interdisciplinary Computing and Complex BioSystems (ICOS)

ICOS carries out research at the interface of computing science and complex biological systems. We seek to create the next generation of algorithms that provide innovative solutions to problems arising in natural or synthetic systems. We do this by leveraging our interdisciplinary expertise in machine intelligence, complex systems and computational biology and pursue collaborative activities with relevant stakeholders.

Scalable Computing

The Scalable Systems Group creates the enabling technology we need to deliver tomorrow's large-scale services. This includes work on:
-Scalable cloud computing
-Big data analytics
-Distributed algorithms
-Stochastic modelling
-Performance analysis
-Data provenance
-Concurrency
-Real-time simulation
-Video game technologies
-Green computing

Secure and Resilient Systems

The Secure and Resilient Systems group investigates fundamental concepts, development techniques, models, architectures and mechanisms that directly contribute to creating dependable and secure information systems, networks and infrastructures. We aim to target real-world challenges to the dependability and security of the next generation information systems, cyber-physical systems and critical infrastructures.

Teaching Innovation Group

The Teaching Innovation Group focusses on encouraging, fostering and pursuing innovation in teaching computing science. Through this group, your research will focus on pedagogy and you will apply your research to maximising the impact of innovative teaching practices, programmes and curricula in the School. Examples of innovation work within the group include:
-Teacher training and the national Computing at School initiative
-Outreach activities including visits to schools and hosting visits by schools
-Participation in national fora for teaching innovation
-Market research for new degree programmes
-Review of existing degree programmes
-Developing employability skills
-Maintaining links with industry
-Establishing teaching requirements for the move to Science Central

Research Excellence

Our research excellence in the School of Computing Science has been widely recognised through awards of large research grants. Recent examples include:
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Cloud Computing for Big Data Doctoral Training Centre
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Digital Civics
-Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC) Research Grant: a £10m project to look at novel treatment for epilepsy, confirming our track record in Systems Neuroscience and Neuroinformatics.

Accreditation

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.

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The MSc in Cyber Security and Management is designed for those wishing to develop a career as a cyber security professional, or to take a leading technical or managerial role in an organisation critically dependent upon data and information communication technology. Read more

Designed for

The MSc in Cyber Security and Management is designed for those wishing to develop a career as a cyber security professional, or to take a leading technical or managerial role in an organisation critically dependent upon data and information communication technology.

It is suitable for those from a computer science or information technology education background. The programme is also able to cater for those with no formal studies in computer science but where significant interest in cyber security can instead be demonstrated.

The Course Provides:

1. Cyber Security in the UK has become a ‘tier 1’ priority alongside international terrorism and major national incidents. The serious threats emerging from the cyber-sphere are a recognised phenomenon worldwide and as such studies in cyber security are strategically important on a global scale.

2. Our goal for the MSc programme is to give focus to the strategic deployment and implementation of Cyber Security within an organization. We want to develop strategic thinkers who understand the Cyber threat to an organization and its resources and are able to build and support secure systems that support the strategic growth of a business.

3. The course covers all aspects of Cyber Security including network security, computer security and information security. You will learn the most important technical concepts of security—such as encryption, intrusion detection, penetration testing, access control, digital forensics and investigation, risk management, security governance and network security.

4. Alongside this, the course focuses on the business context so that students can progress their careers more rapidly through organisations and aim very particularly at management positions.

When you study the MSc Cyber Security and Management at Warwick, you will gain an unparalleded exposure to industry. All taught modules contain considerable input from industry experts who, through case studies and guest lectures, contribute to the design and delivery of material making for a vey rich learning environment.

An example of some of the companies involved in the CSM programme since it was launched in 2012 include HP, Amethyst Consulting, Deep Secure Ltd, Siskin Technology, SOCA (Serious Organised Crime Agency), CSC, VMware, OCSIA, Nottingham Police, Mozilla, Metropolitan Police, Kaspersky, Berwin Leighton Paisner, Telefonica, IBM, Blackstage Forensics, Derbyshire NHS Trust and Nettitude.

You will have additional opportunity to engage with industry through industry visits, conferences, and mentoring or advice from industry experts at key stages of your work.

Course Content

Students study nine taught modules as part of the programme of study.
Core Modules:
1. Security Architectures and Network Defence
2. Cryptosystems and Data Protection
3. Information Risk Management and Governance
4. Industrial Espionage and Counterfeiting
5. Digital Forensics

Elective Modules (3 from this list):
1. Cyber Intelligence and Operations
2. Cyber-Physical Systems
3. Enterprise Cyber Security
4. Globalisation and Outsourcing
5. Financial Analysis and Control Systems
6. Organisations, People and Performance
7. Leadership

A ninth module to be selected from the full list of WMG elective modules.

Learning Style

The taught component of the course is highly interactive and varied with a mixture of lectures, syndicate or group work, practical and lab based work, and technology enabled learning.
Class sizes are kept to a maximum of 30 students per class.
Module leaders are experts in their fields and are supported by external speakers working in organisations at the forefront of their fields.
Assessment is through Post Module Assignment based on the learning objectives of each respective module.
50% of the Masters credit is achieved through your individual project or dissertation, for which you will have close 1-1 supervision
Each module will usually be delivered in intensive one-week blocks so you are fully immersed in the subject area for that period. These one-week sessions are scheduled at intervals from October through to June.

After Your Graduate

Graduates can expect to go on to work within corporate information - security and technology teams, consultancies, government information-security departments, management tracks in information critical organisations and cyber security related research.

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Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies. Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. Read more
Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies.

Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. As well as anyone who holds an undergraduate degree in technology-based disciplines such as Computer Science, Software Engineering, Web Technologies, Computer Engineering, Mathematics and Electronics.

This masters is unique as it provides you with a fundamental understanding of the architectures of Big Data systems as well as developing the enhanced skills in software application development and data analytics solutions that you need.

It is our aim to increase skills in the new technology areas that business and industry are rapidly adopting. These include big data architectures, cloud computing, web technologies, data analytics (especially SAS and IBM Watson Analytics), big data computing platforms and the ever-expanding sources of data related to the Internet of Things.

This course has several different available starts and study formats - please view the relevant web-page for more information:
SEPTEMBER 2017 (Part Time) - http://www.gcu.ac.uk/ebe/study/courses/details/index.php/P02870-1PTA-1718/Big_Data_Technologies_(Part-time)?utm_source=ZZZZ&utm_medium=web&utm_campaign=courselisting

JANUARY 2018 (Full Time) - http://www.gcu.ac.uk/ebe/study/courses/details/index.php/P02860-1FTAB-1718/Big_Data_Technologies?utm_source=ZZZZ&utm_medium=web&utm_campaign=courselisting

JANUARY 2018 (Part Time) - http://www.gcu.ac.uk/ebe/study/courses/details/index.php/P02870-1PTAB-1718/Big_Data_Technologies_(Part-time)?utm_source=ZZZZ&utm_medium=web&utm_campaign=courselisting

Programme Description

The MSc in Big Data Technologies equips students with the fundamental knowledge and practical skills required to enter the exciting and challenging world of Big Data.

The programme takes a technology-focused approach to help students gain valuable skills that can be applied immediately within business and industry. Students will also build expertise in the key enabling technologies of cloud computing and will gain skills in one of the most exciting current areas of Big Data computing, the Internet of Things.

Why Study this Programme

This programme will equip students with the fundamental knowledge and skills of the core technologies for harnessing the big data challenges, including capture, curation, storage, integration, sharing, search, analysis, mining of large distributed unstructured datasets.

Studies on this programme are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cyber security, Internet of Things and cyber-physical systems. Of parallel importance in our programme is to cultivate the professionalism which is expected within the industry.

With all the future-proofing capabilities synthesised coherently together, graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse big data application domains.

What you'll learn

Students complete six taught modules.

Trimester A:
-Cloud Computing and Web Services
-Big Data Landscape
-Data Analytics.

Trimester B:
-Big Data Platforms
-Internet of Things
-IT Professional Issues and Project Methods.

Trimester C:
-MSc Dissertation

Work Placement

Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.

Assessment

Assessment is used to demonstrate achievement of learning outcomes. The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.

Career Opportunities

Graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse Big Data application domains.

This programme provides key skills for those seeking employment or career enhancement as Big Data systems developers, architects and administrators, and Big Data technologist for businesses and organisations in diverse domains from engineering industries, environmental surveillance, smart cities, to service type industries.

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The MSc in Cyber Security Engineering is designed for those wishing to develop a career as a cyber security professional. Cyberspace comprises the network of digital devices, used to store, modify and communicate information. Read more

Designed for

The MSc in Cyber Security Engineering is designed for those wishing to develop a career as a cyber security professional.

Cyber Security

Cyberspace comprises the network of digital devices, used to store, modify and communicate information. It is global, interactive and completely changes our environment. It extends beyond the Internet, mediating interaction between individuals and groups.
Our world is increasingly shaped by cyberspace. Opportunities for interaction are emerging in ways, only imagined by previous generations. As the influence of cyberspace in our lives continues to grow, so does the associated security risk.
As organisations worldwide harness the opportunities of cyberspace, they create huge demand for cyber security professionals. Cyber security professionals who can function at various strata within an organisation - server room, operations room, board room - you choose. Their task is beguilingly simple: enable the good and prevent the bad.

GCHQ Certification

GCHQ, the UK government's National Technical Authority for Information Assurance, identified the shortage of cyber professionals as a concern that needed to be addressed. Part of their strategy was to identify cyber security master's courses that would "... help prospective students make better informed decisions when looking for a highly valued cyber security qualification".

Course Content

You will study a broad range of cyber security topics. Some focus on technology, some on people, some on organisations. Insofar as possible, we seek to avoid teaching topics in silos of narrow expertise. Throughout, the practical application of insight is valued equally with abstract analytical skill. The following should give you a sense of the course content:
◾Cryptography
◾Counterfeiting
◾Risk
◾Digital forensics
◾Governance
◾Data protection
◾Network security
◾Intelligence
◾The enterprise cyber perspective
◾Security architecture
◾Industrial espionage
◾Cyber-physical systems
◾Standards and guidance
◾Cyber security research

Teaching Style

Tutors adopt their own distinctive style within their taught weeks. Most modules are taught by more than one tutor, which, together with the wide range of guest speakers, gives real breadth of insight into any topic. The external input is especially evident in the Enterprise Cyber Security module where colleagues from IBM make a substantial contribution to the week's activities.

After You Graduate

Graduates can expect rapid career progression in within a wide range of organisations relating to cyber security in a range of roles.

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Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies. Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. Read more
Study MSc Big Data Technologies and enter the expanding world of Big Data, Data Analytics and Cloud Technologies.

Available for full-time and part-time study, this course is ideal for current practitioners who have good experience in software development and wish to enhance their skills. As well as, anyone who holds an undergraduate degree in technology-based disciplines such as Computer Science, Software Engineering, Web Technologies, Computer Engineering, Mathematics and Electronics.

Unlike many data science MSc courses, this masters provides you with a fundamental understanding of the architectures of Big Data systems as well as the enhanced skills in software application development and data analytics solutions that you need.

It is our aim to increase skills in the new technology areas that business and industry are rapidly adopting. These include big data architectures, cloud computing, web technologies, data analytics (especially SAS and IBM Watson Analytics), big data computing platforms and the ever-expanding sources of data related to the Internet of Things.

Programme Description

The MSc in Big Data Technologies equips students with the fundamental knowledge and practical skills required to enter the exciting and challenging world of Big Data.

The programme takes a technology-focused approach to help students gain valuable skills that can be applied immediately within business and industry. Students will also build expertise in the key enabling technologies of cloud computing and will gain skills in one of the most exciting current areas of Big Data computing, the Internet of Things.

Work Placement

Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.

Assessment

Assessment is used to demonstrate achievement of learning outcomes. The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.

Career Opportunities

Graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse Big Data application domains.

This programme provides key skills for those seeking employment or career enhancement as Big Data systems developers, architects and administrators, and Big Data technologist for businesses and organisations in diverse domains from engineering industries, environmental surveillance, smart cities, to service type industries.

Why Study this Programme

This programme will equip students with the fundamental knowledge and skills of the core technologies for harnessing the big data challenges, including capture, curation, storage, integration, sharing, search, analysis, mining of large distributed unstructured datasets.

Studies on this programme are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cyber security, Internet of Things and cyber-physical systems.

Of parallel importance in our programme is to cultivate the professionalism which is expected within the industry.

With all the future-proofing capabilities synthesised coherently together, graduates of the MSc in Big Data Technologies will be amongst the most highly skilled ICT graduates, responding confidently to the needs and challenges in diverse big data application domains.

What you'll learn

Students complete six taught modules.

Trimester A:
-Cloud Computing and Web Services
-Big Data Landscape
-Data Analytics

Trimester B:
-Big Data Platforms
-Internet of Things
-IT Professional Issues and Project Methods

Trimester C:
-MSc Dissertation

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The future of information and communication technology (ICT) is driven by mobile and networked embedded systems. Read more

About Mobile and Embedded Systems

The future of information and communication technology (ICT) is driven by mobile and networked embedded systems: tomorrow’s digital cities, Industry 4.0, cyber-physical systems (CPS) and the Internet of Things (IoT) will all depend on embedded sensing of real-world phenomena, in-situ computation as well as automated information exchange and data distribution using machine-to-machine (M2M) com­munications between local and distributed control systems and machinery.

The ‘smart grid’ is one example of an application for future embedded systems, as it uses real-time sensing of the available renewable energy to determine where energy is to be routed across the power grid and controls intelligent machinery to increase production during peak times; this requires that internet-connected smart meters are installed in industrial plants and private homes alike to facilitate real-time sensing and control of technical systems.

Another exciting area of application for embedded systems is mobile and wearable technology, which allows users to access and manipulate information ‘on the go’ as the system provides relevant and timely information — indeed, this is one of the main purposes of mobile information technology such as smartphones and tablet computers. Additional meaning for this Human-Computer Interaction (HCI) is generated by the context of the device, the user, the location and many more factors, all of which are sensed and computed by a plenitude of embedded sensors and collocated or connected systems.

Wearable devices such as fitness trackers and smart watches collect bio-physiological and health-related data to facilitate novel applications, including smart contact lenses and feedback systems for the learning of physical activities. At the same time, increasing cross-device interoperability means that users of head-mounted augmented reality and virtual reality displays can, for instance, use their entire smartphone screen as a keyboard and have the typed text displayed on augmented reality glasses.

Programme content

The programme is divided into three module groups with core and elective modules. These are:

1. Human-Computer Interaction
2. Systems Engineering
3. Data Processing, Signals and Systems

Features

- Excellent rankings for computer science, e.g. in U-Multirank and the CHE rankings
- A strongly research-oriented two-year programme with a modern, broad range of subjects
- Allows flexible interest-based selection of modules from the groups ‘Human-Computer Interaction’, ‘Systems Engineering’ and ‘Data Processing, Signals and Systems’
- A fully English-taught programme
- An outstanding staff-student ratio
- Participation in cutting-edge research projects
- Excellent research and teaching infrastructure
- An extensive network of partnerships with academic institutions and businesses worldwide
- A great student experience in Passau, the ‘City of Three Rivers’

Language requirements

Unless English is your native language or the language of your secondary or undergraduate education, you should provide an English language certificate at level B2 CEFR, e.g. TOEFL with a minimum score of 567 PBT, 87 iBT or ITP 543 (silver); IELTS starting from 5.5; or an equivalent language certificate.

To facilitate daily life in Germany, it would be beneficial for you to have German language skills at level A1 CEFR (beginner’s level). If you do not have any German skills when starting out on the programme, you will complete a compulsory beginner’s German course during your first year of study.

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