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Masters Degrees (Web Intelligence)

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The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. Read more
The programme is for students with computer science, mathematics, science or engineering backgrounds and good knowledge of computer programming. To improve the ability to solve a broad range of challenging computational problems related to advanced reasoning systems for the web by providing a thorough knowledge of techniques for developing intelligent software, and to provide a broad introduction to web intelligence.

Key benefits

• Web Intelligence has been recognised as a new direction for scientific research and development to explore the fundamental roles as well as practical impacts of the use of artificial intelligence techniques in advanced information technology.

• The programme will cover aspects of web intelligence through internet computing and the web on the one hand, and intelligent agent systems on the other.

• The strength of the programme is the integration of modules on fundamental internet technologies with the unique profile of the complementary aspects of artificial intelligence, algorithmic issues of the web, policies and norms, and agents and multi-agent systems that directly reflect our research expertise.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/web-intelligence-msc.aspx

Course detail

- Description -

This programme provides students with a broad understanding of web intelligence and a thorough knowledge of the techniques for developing intelligent software. It is built around taught core modules such as Agents and Multi-agent Systems, Artificial Intelligence and Software Engineering of Internet Applications, which are complemented by a wide range of optional modules that will broaden your understanding of web intelligence. The final part of the programme is an individual project which is closely linked with the Department's research activities.

- Course purpose -

A graduate in computer science, mathematics, science or engineering with good knowledge of computer programming, this MSc will provide you with the practical knowledge and expertise to enable you to evaluate, design and build intelligent software for the web. Research for your individual project will provide valuable preparation for a career in research or industry.

- Course format and assessment -

Lectures; tutorials; seminars; laboratory sessions; optional career planning workshops. Assessed through: coursework; written examinations; final project report.

Career prospects

Via the Department’s Careers Programme, students are able to network with top employers and obtain advice on how to enhance career prospects. Our graduates have gone on to have very successful careers in industry and research. Recent employers have included general software consultancy companies, specialised software development companies and the IT departments of large institutions (financial, telecommunications and public sector). Other graduates have entered into the field of academic and industrial research in software engineering, bioinformatics, algorithms, artificial intelligence and computer networks.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

About Postgraduate Study at King’s College London:

To study for a postgraduate degree at King’s College London is to study at the city’s most central university and at one of the top 20 universities worldwide (2015/16 QS World Rankings). Graduates will benefit from close connections with the UK’s professional, political, legal, commercial, scientific and cultural life, while the excellent reputation of our MA and MRes programmes ensures our postgraduate alumni are highly sought after by some of the world’s most prestigious employers. We provide graduates with skills that are highly valued in business, government, academia and the professions.

Scholarships & Funding:

All current PGT offer-holders and new PGT applicants are welcome to apply for the scholarships. For more information and to learn how to apply visit: http://www.kcl.ac.uk/study/pg/funding/sources

Free language tuition with the Modern Language Centre:

If you are studying for any postgraduate taught degree at King’s you can take a module from a choice of over 25 languages without any additional cost. Visit: http://www.kcl.ac.uk/mlc

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Learning how to build the intelligence used to power the future of the Web. The Web has provided us with novel ways to maintain our social networks, rapidly search for information, and make purchases from the comfort of our own home. Read more
Learning how to build the intelligence used to power the future of the Web.
The Web has provided us with novel ways to maintain our social networks, rapidly search for information, and make purchases from the comfort of our own home. Most of us take these technologies for granted. However, for the Web to function as it does numerous problems had to be solved: which pages should surface given your search query? Which status updates will you enjoy most? Or, how do we make sure you find the products that you where looking for?
These questions are solved using a combination of machine learning, and an understanding of users. As our use of the Web steadily grows, new questions are continuously emerging. Smarter and faster solutions to empower an intelligent Web are needed. In the Master’s specialisation in Web and Language Interaction you’ll learn the building blocks you’ll need to answer resolve future problems that arise on the Web. In this you’ll learn to understand the psychological, technical and statistical aspect of data science and other Web issues.
The key course in this specialisation is the new AI at the Webscale course, in which AI techniques are studied in the context of streaming and massive data. This course is complemented by the App-Lab course, aimed at understanding how Apps are set-up, built and evaluated. Covering human cognition, a choice of courses in psycho-linguistics is offered in line with the broad expertise within the Donders Institute.

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

Why study Web and Language Interaction 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.

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

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

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

- 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 debate and develop their projects. Every student also receives personal guidance and supervision from a member of our expert staff.

Our approach to this field

Language Information and Communication Technology lies at the basis of innumerable innovations in our society and has provided remarkable new services (like social media) and new products (like smart phones and tablets). Traditionally, applications of Artificial Intelligence used to be limited to micro worlds and toy systems. The horizon has now been widely extended to distribute mass applications of AI techniques. These developments are supported by a general availability of computation power and connectivity in the form of the web, social media, big data, wireless, and mobile platforms with input and output in many modalities.

Human-human and human-computer communication can be found in natural language applications like in the speech driven free-text systems such as Watson, and Siri, in brand sentiment detection and epidemic monitoring from tweets. But communication is also crucial for web applications and Apps that personalise information and make it accessible with other means. Examples thereof are voter guides, recommendation systems, click stream analysis, crowd sourcing and demand aggregation, e-therapy, e-inclusion, avatars with speech synthesis and recognition, gesture and emotion. Technical issues are e.g. map/ reduce architecture for massive data processing and emerging technologies like the semantic web.

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: Booking.com, Webpower, Google, Facebook, Philips, Booking.com, Philips, Rabobank. Some students have even gone on to start their own companies.

Job positions

Examples of jobs that a graduate of the specialisation in Web and Language Interaction could get:
- PhD researcher, for example, on enhancing speech recognition using semantic knowledge or in user interaction design for patient doctor communication in a virtual hospital
- Data Scientist in a web start-up
- Developer for Computer Aided Language Learning
- EU R&D programme leader on machine translation of natural language
- Developer of intelligent software for music studios

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, Finland and the United States.

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

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This course is your opportunity to specialise in the development of web-based software systems that use databases. Read more
This course is your opportunity to specialise in the development of web-based software systems that use databases. During your time with us, you will gain a critical awareness of the methodologies, tools and techniques used for the development of web-based computer systems and an advanced understanding of the techniques used for the development, evaluation and testing of databases.

The course also develops an awareness of the latest developments in the field of advanced databases, data mining and data warehousing. You will also gain substantial knowledge and skills in the deployment of SAS business intelligence software leading towards SAS data miner accreditation, and learn what the Semantic Web and Linked Data are, together with what these technologies enable.

Key benefits:

• The course gives you hands-on experience in design and implementation of databases in both Oracle and Microsoft SQL Server DBMS and prepares you to obtain DBA certification
• You learn how to design and implement a web application using ASP.NET, Microsoft SQL Server, and PHP with My SQL
• You learn the data mining techniques to mine data in different application domains using most popular data mining tools.

Visit the website: http://www.salford.ac.uk/pgt-courses/databases-and-web-based-systems

Suitable for

This course is for students who want to become trained professionals:

• In designing and implementing database systems in Oracle Micro Soft SQL Server DBMS and who want to be prepared to obtain DBA certification
• In designing and implementing a web application using ASP.NET, Microsoft SQL Server, and PHP with My SQL
• With hands-on experience in data mining techniques to mine data in different application domains using the most popular data mining tools.

Programme details

This course covers a very comprehensive range of topics split in to four large modules worth 30 credits each plus the MSc Project. External speakers from blue-chip and local companies will give seminars to complement your learning, that will be real-world case studies related to the subjects you are studying in your modules. These are designed to improve the breadth of your learning and often lead to ideas that you can develop for your MSc Project.

Format

Teaching on this course takes the form of lectures, individual and group class work, topical class discussions and critical case study evaluation.

You will gain hands-on lab experience of using and setting up databases and web-based systems. What’s more, tutorials will give you practice in solving the theoretical and design problems associated with these systems.

Module titles

• Advanced Databases
• Web-Based Software Development
• Semantic Web and Information Extraction
• Business Intelligence
• MSc Project

Assessment

• Coursework 60%
• Examinations 40%

Career potential

With this qualification, you’ll be equipped as web/database designer and programmer, data analytics and miner among other roles. Your experience will be in high demand across all industrial and commercial sectors.

Previous students have gone on to work with companies including British Airways, Google, Hewlett-Packard, Oracle and other IT firms.

How to apply: http://www.salford.ac.uk/study/postgraduate/applying

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Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems. Read more

Overview

Understanding naturally intelligent systems, building artificially intelligent systems, and improving the interactions between humans and artificial systems.

As humans, we may be intrigued by the complexity of any daily activity. How do we perceive, act, decide, and remember? On the one hand, if we understand how our own intelligence works, we can use this knowledge to make computers smarter. On the other hand, by making computers behave more like humans, we learn more about how our own cognition works.

The AI Master’s programme at Radboud University has a distinctly cognitive focus. This cognitive focus leads to a highly interdisciplinary 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.

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

Scientific and practical applications

Slowly the human brain has been revealing its mystery to the scientific community. Now that we are actually able to model and stimulate aspects of cognition, AI researchers have gained a deeper understanding of cognition. At the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres, we train our students to become excellent researchers in this area.

At Radboud University we also teach students how to develop practical applications that will become the next generation of products, apps, therapies and services. Our department has been awarded several prizes for its pioneering role in bringing innovations from science to society, e.g. in Assistive Technology for people with disabilities. You’ll be taught the skills needed to conduct and steer such innovation processes. Many Master’s research projects have both a scientific and a practical component.

Specialisations

Computational modelling is the central methodology taught and used in this programme. Depending on the area of study, the computational models can range from behavioural models of millions of individuals interacting on the web, to functional models of human or robot decision-making, to models of individual or networks of artificial neurons. At Radboud University we offer the following three specialisations (on campus simply known as Computation, Robot and Web):

- Computation in Neural and Artificial Systems
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.

- Robot Cognition
Understand all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.

- Web and Language Interaction
Learn how to build the intelligence used to power the future of the Web.

Research project and Internship

To finalise your AI master's programme, you have the choice of either an Internship (18EC) and Research Project (30EC) or a single larger Extended Research Project (48EC). During the internship you have the chance to acquire additional AI relevant skills either at a research lab or at a company. During the Research Projects phase, you get to put what you have learned during your master's programme into practice. You can perform your research work in the AI department, at other research departments at the University (e.g. the Behaviour Science Institute or Donders Institute) or at an external company (such as Philips or TNO). You are also encouraged to go abroad for your internship and/or research project (previously students have gone to Stanford University in California and Aldebaran Robotics in Paris). To help you decide on a thesis topic, there is an annual Thesis Fair where academics and companies present possible project ideas.

Job opportunities

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 a university with an AI department. Other graduates have started their own companies or work for companies interested in cognitive design and research.

Find out how to apply here http://www.ru.nl/masters/ai

Meet Radboud University

- Information for international students
Radboud University would like to meet you in your country (http://www.ru.nl/meetus) in order to give all the information you need and to answer any questions you might have about studying in the Netherlands. In the next few months, an advisor of Radboud University will be attending fairs in various countries, always accompanied by a current or former student.
Furthermore, we understand if you would like to see the Radboud Campus and the city of Nijmegen, which is why we organise an Master's Open Day for international students (http://www.ru.nl/openday) which will take place on 5 March 2016.

- Information for Dutch students
Radboud University offers students in the Netherlands plenty of opportunities to get more information on your programme of choice, or get answers to any questions you might have and more. Apart from a Master's Evening and a Master's Day, we also organise Orientation Days and a Master’s Afternoon for HBO students.

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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. Read more
The Advanced Computer Science (Computational Intelligence) MSc programme combines a wide choice of advanced topics in computer science with specialist modules relating to computational intelligence, including logic-based, connectionist and evolutionary artificial intelligence, inspirations from the natural world, practical applications and the philosophy of machine reasoning.

While studying a taught Master’s programme at the School of Computing, you can gain work experience through our industrial placement scheme or with the Kent IT Consultancy (KITC), which provides a project-based consultancy service to businesses in the region. We have strong links with industry including Cisco, IBM, Microsoft and Oracle and are among the top ten in the UK for graduate employment prospects.

The programme is aimed at graduates considering a career in research and development. It would also provide an excellent foundation for PhD study.

This programme is available with an optional industrial placement.

Visit the website https://www.kent.ac.uk/courses/postgraduate/249/advanced-computer-science-computational-intelligence

About the School of Computing

Our world-leading researchers, in key areas such as systems security, programming languages, communications, computational intelligence and memory management, and in interdisciplinary work with biosciences and psychology, earned us an outstanding result in the most recent national research assessment.

In addition, two of our staff have been honoured as Distinguished Scientists by the ACM and we have also held Royal Society Industrial Fellowships.

As an internationally recognised Centre of Excellence for programming education, the School of Computing is a leader in computer science teaching. Two of our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education. We are also home to two National Teaching Fellows, to authors of widely used textbooks and to award-winning teaching systems such as BlueJ.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

CO885 - Project Research (15 credits)
CO880 - Project and Dissertation (60 credits)
CO881 - Object-Oriented Programming (15 credits)
CO871 - Advanced Java for Programmers (15 credits)
CO832 - Data Mining and Knowledge Discovery (15 credits)
CO836 - Cognitive Neural Networks (15 credits)
CO837 - Natural Computation (15 credits)
CO884 - Logic and Logic Programming (15 credits)
CO838 - Internet of Things and Mobile Devices (15 credits)
CO841 - Computing Law, Contracts and Professional Responsibility (15 credits)
CO846 - Cloud Computing (15 credits)
CO847 - Green Computing (15 credits)
CO528 - Introduction to Intelligent Systems (15 credits)
CO545 - Functional and Concurrent Programming (15 credits)
CO641 - Computer Graphics and Animation (15 credits)
CO645 - IT Consultancy Practice 2 (15 credits)
CO834 - Trust, Security and Privacy Management (15 credits)
CO874 - Networks and Network Security (15 credits)
CO876 - Computer Security (15 credits)
CO889 - C++ Programming (15 credits)
CO890 - Concurrency and Parallelism (15 credits)
CO892 - Advanced Network Security (15 credits)
CO894 - Development Frameworks (15 credits)
CO899 - System Security (15 credits)
PL583 - Philosophy of Cognitive Science and Artificial Intelligence (30 credits)

Assessment

Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation, except for the MSc in IT Consultancy for which the practical consultancy work is assessed through a series of reports covering each of the projects undertaken.

Programme aims

This programme aims to:

- enhance the career prospects of graduates seeking employment in the computing/IT sector

- prepare you for research and/or professional practice at the forefront of the discipline

- develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)

- develop a variety of advanced intellectual and transferable skills

- equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Careers

Students can gain practical work experience as part of their degree through our industrial placements scheme and Kent IT Consultancy. Both of these opportunities consolidate academic skills with real world experience, giving our graduates a significant advantage in the jobs market.

Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

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

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Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. Read more
Drawing on our research excellence in this area, this innovative programme of study in big data and business intelligence is designed to give graduates a competitive advantage in the modern, fast growing business domain. This is one of the first MSc programmes in the UK covering these leading-edge technologies. The programme provides students with the deeper knowledge, advanced skills and understanding that will allow them to contribute to the development and design of big data systems as well as distributed/internet-enabled decision support application software systems, using appropriate technologies, architectures and techniques (e.g. data analytics, business intelligence, NoSQL, data mining, data warehousing, distributed data management and technologies, Hadoop, etc.).

Additionally, the programme enables students to understand and assess the security and legal implications of e-commerce applications and provides students with appropriate knowledge of business and commerce relevant to transacting business on the internet. The courses take a software engineering approach to the construction of applications and focus on modern software engineering methods, tools and techniques that enable an integrated life-cycle software development view.

Through our short course centre opportunity may also be provided to study for the following professional qualifications: Microsoft Technology Associate Exams; Certified Professional Java SE Programmer; Java Certified Associate; Oracle Certified Associate (OCA).

Visit the website http://www2.gre.ac.uk/study/courses/pg/com/cgbdbi

Computing - General

Come and study in the award-winning Department of Computing & Information Systems on the magnificent Greenwich Campus. Welcoming home and international students from all backgrounds, CIS provides an exciting, diverse and friendly environment in which to study.

The latest university league table published in the Sunday Times, has rated the computer science department as seventh in the UK for teaching excellence.

What you'll study

Full time
- Year 1:
Students are required to study the following compulsory courses.

PG Project (CIS) (60 credits)
Data Warehousing (15 credits)
Database Architectures and Administration (15 credits)
Database Tools (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)
Big Data (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

Students are required to choose 15 credits from this list of options.

Requirements Analysis & Methods (15 credits)
Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)

Students are required to choose 15 credits from this list of options.

System Modelling (15 credits)
Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Multi-structured Data and NoSQL Technology (15 credits)

Part time
- Year 1:
Students are required to study the following compulsory courses.

Database Architectures and Administration (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)
Big Data (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

- Year 2:
Students are required to study the following compulsory courses.

PG Project (CIS) (60 credits)
Data Warehousing (15 credits)
Database Tools (15 credits)

Students are required to choose 15 credits from this list of options.

Requirements Analysis & Methods (15 credits)
Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)

Students are required to choose 15 credits from this list of options.

System Modelling (15 credits)
Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Multi-structured Data and NoSQL Technology (15 credits)

Fees and finance

Your time at university should be enjoyable and rewarding, and it is important that it is not spoilt by unnecessary financial worries. We recommend that you spend time planning your finances, both before coming to university and while you are here. We can offer advice on living costs and budgeting, as well as on awards, allowances and loans.

Assessment

Students are assessed through examinations, coursework and a project.

Professional recognition

This programme is accredited by the British Computer Society (BCS). On successful graduation from this degree, the student will have fulfilled the academic requirement for registration as a Chartered IT Professional (CITP) and partially fulfilled the education requirement for registration as a Chartered Engineer (CEng) or Chartered Scientist (CSci). For a full Chartered status there are additional requirements, including work experience. The programme also has accreditation from the European Quality Assurance Network for Informatics Education (EQANIE).

Career options

Graduates from this programme can pursue careers as data scientists, database designers and administrators, consultants, senior team members, programmers, analysts.

Find out how to apply here - http://www2.gre.ac.uk/study/apply

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The course provides an opportunity to develop the skills suitable for a career in Computing with specialist subjects in software development and business intelligence (data science/data analysis). Read more
The course provides an opportunity to develop the skills suitable for a career in Computing with specialist subjects in software development and business intelligence (data science/data analysis).

It allows those who wish to apply their knowledge and expertise in a technical environment to develop the computing and business intelligence skills needed to match software solutions to the needs of business. The course is suitable for graduates wishing to transition into an IT career from other disciplines, as well as for candidates wishing to extend their existing IT experience with a formal Computing qualification.

You will develop skills in business intelligence/data science, software development, database systems, and web programming, as well as the research and development skills required to undertake a sustained piece of data science or software development project work. The course is designed to provide the core computing and business intelligence knowledge and skills required to work within the IT industry, using software development and business intelligence tools and techniques to extend and enhance the knowledge and skills of non-computing graduates.

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This exciting new programme explores developments in cloud based and mobile commerce that are changing the way businesses will operate in the future. Read more

About the course

This exciting new programme explores developments in cloud based and mobile commerce that are changing the way businesses will operate in the future. The Business Intelligence and Social Media MSc draws together technology and business perspectives in order to understand the implications for social-media enabled business.

The course helps students prepare for a career in business and management within and beyond the IT sector by gaining technical skills and an appreciation of the crucial role social web technologies play in today’s organisations and their ability to transform business processes.

Aims

You will develop sound knowledge and understanding of new-media related business practices and transferable skills designed to meet the challenges of employment within the global economy.

You will gain understanding of the importance of information and mass communications technologies to the operations of modern businesses of all kinds.

You will be encouraged to reflect on the relevance of concepts to business and apply your newly developed skills in advance studies or professional practice. Successful graduates of the course progress to leadership and decision making roles in industrial organisations or develop successful consultancy and advisory businesses of their own.

Practitioners seeking a more commercially relevant and technology oriented master’s qualification in the area of new business technologies rather than an MBA find this course of interest.

Course Content

The MSc consists of both compulsory and optional modules, a typical selection can be found below. Modules can vary from year to year, but these offer a good idea of what we teach.

Compulsory Modules

Professional Consultancy in Business Intelligence and Social Media
Social Media
Business Intelligence
Mobile, Social Media and Cloud Services
Knowledge Management, Social Networks and Innovation
Entrepreneurship
Understanding Business and Management Research
Dissertation

Optional

Choose one module from these:

Global Outsourcing
International Business Ethics and Corporate Governance
Strategic Marketing Management
Global Diversity Management

Special Features

Brunel Business School won the Times Higher Education Awards Business School of the Year 2013

The course offers:

Curriculum focus on social media in business.
Teaching with and through social media.
Technologies introduced from non-tech perspective.
Focus on consultancy and entrepreneurship.
Opportunities for students to practice and develop problem analysis, solution design, advisory and communication skills, as well as to become familiar with business models and the life-cycle of business development.

Information Systems Evaluation and Integration Group

Academics who teach on this exciting programme are part of the Information Systems Evaluation and Integration Group which is a research centre of excellence that supports a number of Engineering and Physical Sciences Research Council (EPSRC) funded networks and projects. This group is housed in the Brunel Business School in collaboration with the excellent-rated (RAE score 5) School of Information Systems, Computing and Mathematics. ISEing is the first multi-disciplinary research group to receive government funding in the areas of Information Systems Evaluation, Enterprise Integration and eGovernment.

Teaching

The course is structured so that full-time students take four 15 credit modules per term, plus a 60 credit dissertation module in term 3. Each 15 credit module demands 150 hours of study comprised of 22 hours of tutor arranged contact time and a minimum of 128 hours of non-contact student managed time. Each module has its own form of assessment held at the end of the term in which the module runs, and can include essays, projects and group assignments. The dissertation is an extended research oriented task conducted individually and offers the opportunity for students to undertake in-depth investigation in to a topic of their choosing. Students may choose to develop a project in collaboration with an industrial partner, which can be focused on business solutions of practical relevance (rather than theoretical research).

Modes of Study

1-year full-time in September: The taught element of the course (September to April) includes eight modules; delivery will be by a combination of lectures, seminars and tutorials/group work. A further four months (May to September) is spent undertaking the dissertation.

1-year full-time in January: The taught element of the programme includes 8 modules which are delivered in two terms (four in January to April, and four in September to December); delivery will be by a combination of lectures, seminars and tutorials/group work. The dissertation is undertaken May to August, and then can be completed January to March after the second teaching term.

Graduate School Workshops

In addition to the events and training sessions organised within the Business School, master's students have exclusive access to the workshops and skills training provided by the Brunel University’s Graduate School.

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

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

Course description

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

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

Teaching and learning

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

Coursework and assessment

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

Facilities

-Newly refurbished computing labs furnished with modern desktop computers
-Access to world leading academic staff
-Collaborative working labs complete with specialist computing and audio visual equipment to support group working
-Over 300 Computers in the School dedicated exclusively for the use of our student
-An Advanced Interfaces Laboratory to explore real time collaborative working
-A Nanotechnology Centre for the fabrication of new generation electronic devices
-An e-Science Centre and Access Grid facility for world wide collaboration over the internet
-Access to a range of Integrated Development Environments (IDEs)
-Specialist electronic system design and computer engineering tools

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If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. Read more

Your programme of study

If you want to get involved in our next industry revolution - Industry 4.0 this degree will go a long way to providing you with many skills needed in this high growth industry area which has continued from where the mass communications revolution. You must have covered either computer science or electrical and electronic engineering as your first degree or a suitable combination to study this Master's degree. The digital age is changing the way we live, communicate, interact and our quality of life rapidly. Cloud based networks are now normal, autonomous vehicles are being explored, visual recognition, GIS aligning to our search interests, data mining to inform us automatically at any point in time what is happening around us and new methods to inform us of danger, awareness, alerts and so on.

Artificial Intelligence provides in depth knowledge of data mining, natural language, information visualisation and communication used in Industry 4.0 innovation industries such as autonomous vehicles, sensor data collection and computation, visual computer recognition software and machine to machine technologies.

Courses listed for the programme

SEMESTER 1
Compulsory Courses
Foundations in AI
Machine Learning
Evaluation Systems of AI Systems
Engineering of AI Systems

SEMESTER 2
Compulsory Courses
Data Mining and Visualisation
Natural Language Generation
Software Agents and Multi-Agent Systems
Knowledge Representation and Reasoning

SEMESTER 3
You can broaden and deepen your skills with industry client opportunities where possible

Find out more detail by visiting the programme web page
https://www.abdn.ac.uk/study/postgraduate-taught/degree-programmes/1034/artificial-intelligence/

Why study at Aberdeen?

• AI or Artificial Intelligence is part of a major industrial revolution globally, linking to the Internet of Things
• Aberdeen gives you a strong worldwide reputation for teaching in computing science, data science and natural language
generation
• You can be involved in cutting edge innovations which will shape our world in the future

Where you study

• University of Aberdeen

International Student Fees 2017/2018

Find out about fees:
https://www.abdn.ac.uk/study/international/tuition-fees-and-living-costs-287.php

*Please be advised that some programmes have different tuition fees from those listed above and that some programmes also have additional costs.

Scholarships

View all funding options on our funding database via the programme page
https://www.abdn.ac.uk/study/postgraduate-taught/finance-funding-1599.php
https://www.abdn.ac.uk/funding/

Living in Aberdeen

Find out more about:
• Your Accommodation
• Campus Facilities
• Aberdeen City
• Student Support
• Clubs and Societies

Find out more about living in Aberdeen:
https://abdn.ac.uk/study/student-life

Living costs
https://www.abdn.ac.uk/study/international/finance.php

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This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. Read more
This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Course content

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Modules

The following modules are indicative of what you will study on this course.

Core modules
-BIG DATA THEORY AND PRACTICE
-BUSINESS ANALYTICS
-DATA MINING AND MACHINE LEARNING
-RESEARCH METHODS AND PROFESSIONAL PRACTICE
-BUSINESS SYSTEMS POSTGRADUATE PROJECT

Option modules
-ADVANCED BIG DATA ANALYTICS
-BUSINESS OPTIMISATION
-DATA VISUALISATION AND DASHBOARDING
-DATA WAREHOUSING AND OLAP
-DATA REPOSITORIES PRINCIPLES AND TOOLS
-SIMULATION MODELLING: RISK, PROCESSES, AND SYSTEMS
-WEB AND SOCIAL MEDIA ANALYTICS

Associated careers

Graduates can expect to find employment as consultants, decision modelling or advanced data analyst, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (such as GlaxoSmithKline, Prudential, Santander and Unilever), public sector organisations (such as the NHS and primarily care trusts), retail head offices, the BBC, the Civil Service and the host of banks, brokers and regulators that makeup the city, along with all the specialist support consultancies in IT and market research and forecasting, all of the whom us data for the full range of decision making.

Professional recognition

This course is accredited by the British Computer society for partial fulfilment of the academic requirement for Chartered IT professional.

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This research led MSc incorporates traditional and state-of-the-art aspects of artificial intelligence (AI) and machine learning, through a contemporary approach which covers the fundamental aspects of traditional symbolic and sub-symbolic aspects. Read more

Course Summary

This research led MSc incorporates traditional and state-of-the-art aspects of artificial intelligence (AI) and machine learning, through a contemporary approach which covers the fundamental aspects of traditional symbolic and sub-symbolic aspects.

Modules

Semester one: Intelligent Agents; Machine Learning; Foundations of Artificial Intelligence; Computer Vision; Robotic Systems; Evolution of Complexity

Semester two: Advanced Computer Vision; Biological Inspired Robotics; Advanced Machine Learning; Advanced Intelligent Agents; Computational Biology; Computational Finance; Image Processing; Semantic Web Technologies; Simulation Modelling for Computer Science; Biometrics.

Plus three month independent research project culminating in a dissertation

Visit our website for further information...



Read less
This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. Read more
This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course, which builds on the strength of two successful courses on data mining and on decision sciences, is more technology focused, and stretches the data mining and decision sciences theme to the broader agenda of business intelligence.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, through the use of applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within the business intelligence and analytics practices, and know how to adapt to these changes.

Course content

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools and methods. These include warehousing and data mining, distributed data management, and the technologies, architectures, and appropriate middleware and infrastructures supporting application layers. The second theme will enhance your knowledge of algorithms and the quantitative techniques suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop and Oracle.

Taught modules may be assessed entirely through course work, or may include a two-hour exam at the end of the year.

Modules

The following modules are indicative of what you will study on this course.

Core modules
-BIG DATA THEORY AND PRACTICE
-BUSINESS ANALYTICS
-DATA MINING AND MACHINE LEARNING
-RESEARCH METHODS AND PROFESSIONAL PRACTICE
-BUSINESS SYSTEMS POSTGRADUATE PROJECT

Option modules
-ADVANCED BIG DATA ANALYTICS
-BUSINESS OPTIMISATION
-DATA VISUALISATION AND DASHBOARDING
-DATA WAREHOUSING AND OLAP
-DATA REPOSITORIES PRINCIPLES AND TOOLS
-SIMULATION MODELLING: RISK, PROCESSES, AND SYSTEMS
-WEB AND SOCIAL MEDIA ANALYTICS

Associated careers

Graduates can expect to find employment as consultants, decision modelling or advanced data analyst, and members of technical and analytics teams supporting management decision making in diverse organisations. Typical employers include local authorities, PLCs (such as GlaxoSmithKline, Prudential, Santander and Unilever), public sector organisations (such as the NHS and primarily care trusts), retail head offices, the BBC, the Civil Service and the host of banks, brokers and regulators that makeup the city, along with all the specialist support consultancies in IT and market research and forecasting, all of the whom us data for the full range of decision making.

Professional recognition

This course is accredited by the British Computer society for partial fulfilment of the academic requirement for Chartered IT professional.

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Master in BIG DATA. Read more
Master in BIG DATA : Data Analytics, Data Science, Data Architecture”, accredited by the French Ministry of Higher Education and Research, draws on the recognized excellence of our engineering school in business intelligence and has grown from the specializations in Decision Support, Business Intelligence and Business Analytics. The Master is primarily going to appeal to international students, "free movers" or those from our partner universities or for high-potential foreign engineers who are looking for an international career in the domain of Business Analytics.

This program leads to a Master degree and a Diplôma accredited by the French Ministry of Higher Education and research.

Objectives

Business Intelligence and now Business Analytics have become key elements of all companies.

The objective of this Master is to train specialists in information systems and decision support, holding a large range of mathematic- and computer-based tools which would allow them to deal with real problems, analyzing their complexity and bringing efficient algorithmic and architectural solutions. Big Data is going to be the Next Big Thing over the coming 10 years.

The targeted applications concern optimization in the processing of large amounts of data (known as Big Data), logistics, industrial automation, but above all it’s the development of BI systems architecture. These applications have a role in most business domains: logistics, production, finance, marketing, client relation management.

The need for trained engineering specialists in these domains is growing constantly: recent studies show a large demand of training in these areas.

Distinctive points of this course

• The triple skill-set with architecture (BI), data mining and business resource optimization.
• This master will be run by a multidisciplinary group: statistics, data mining, operational research, architecture.
• The undertaking of interdisciplinary projects.
• The methods and techniques taught in this program come from cutting-edge domains in industry and research, such as: opinion mining, social networks and big data, optimization, resource allocation and BI systems architecture.
• The Master is closely backed up by research: several students are completing their end-of-studies project on themes from the [email protected] laboratory, followed and supported by members from the laboratory (PhD students and researcher teachers).
• The training on the tools used in industry dedicated to data mining, operational research and Business Intelligence gives the students a plus in their employability after completion.
• Industrial partnerships with companies very involved in Big Data have been developed:
• SAS via the academic program and a ‘chaire d’entreprise’ (business chair), allowing our students access to Business Intelligence modules such as Enterprise Miner (data mining) and SAS-OR (in operational research).

Practical information

The Master’s degree counts for 120 ECTS (European Credit Transfer System) in total and lasts two years. The training lasts 1252 hours (611 hours in M1 and 641 hours in M2). The semesters are divided as follows:
• M1 courses take place from September until June and count for a total of 60 ECTS
• M2 courses take place from September until mid-April and count for a total of 42ECTS
• A five-month internship (in France) from mid- April until mid- September for 9 ECTS is required and a Master thesis for 9 ECTS.

Non-French speakers will be asked to participate to a one week intensive French course that precedes the start of the program and allows students to gain the linguistic knowledge necessary for daily interactions.

[[Organization ]]
M1 modules are taught from September to June (60 ECTS, 611 h)
• Data exploration
• Inferential Statistics (3 ECTS, 30h, 1 S*)
• Data Analysis (2 ECTS, 2h, 1 S)
• Mathematics for Computer science
• Partial Differential Equations and Finite Differences (3 ECTS, 30h, 1 S)
• Operational Research: Linear Optimization (2 ECTS, 20h, 1 S)
• Combinatory Optimization (2 ECTS, 18h, 1 S)
• Complexity theory (1 ECTS, 9h, 1 S)
• Simulation and Stochastic Process (3 ECTS, 30h, 2 S**)
• Introduction to Predictive Modelling (2ECTS, 21h, 2 S)
• Deterministic and Stochastic Optimization (3 ECTS, 30h, 2 S)
• Introduction to Data Mining (2 ECTS, 21h, 2 S)
• Software and Architecture
• Object-Oriented Modelling (OOM) with UML (3 ECTS, 30h, 1 S)
• Object-Oriented Design and Programming with Java (2 ECTS, 30h, 1 S)
• Relational Database: Modelling and Design (3ECTS, 30h, 1 S)
• PLSQL (2 ECTS, 21h, 2 S)
• Architecture and Network Programming (3 ECTS, 30h, 2 S)
• Parallel Programming (3 ECTS, 30h, 2 S)
• Engineering Science
• Signal and System (3 ECTS, 21 h, 1 S)
• Signal processing (3 ECTS, 30h, 1 S)

• Research Initiation
• Scientific Paper review (1 ECTS, 9h, 1 S)
• Final research project on BIG DATA (5 ECTS, 50h, 2 S)
• Project Management
• AGIL Methods & Transverse Project (2 ECTS, 21h, 2 S)
• Languages and workshops
• French and Foreign languages (6 ECTS, 61h, 1&2 S)
• Personal and Professional Project (1 ECTS, 15, 1 S)
*1 S= 1st semester, ** 2 S= 2nd semester

M2 Program: from September to September (60 ECTS, 641h)
M2 level is a collection of modules, giving in total 60 ECTS (42 ECTS for the modules taught from September to April, plus 9 ECTS for the internship and 9 ECTS for the Master thesis).

Computer technologies
• Web Services (3 ECTS, 24h, 1 S)
• NOSQL (2 ECTS, 20h, 1 S)
• Java EE (3 ECTS, 24, 1S)
Data exploration
• Semantic web and Ontology (2 ECTS, 20h, 1 S)
• Data mining: application (2 ECTS, 20h, 1S)
• Social Network Analysis (2ECTS, 18h, 1S)
• Collective intelligence: Web Mining and Multimedia indexation (2 ECTS, 20h, 2 S)
• Enterprise Miner SAS (2 ECTS, 20h, 2 S)
• Text Mining and natural language (2 ECTS, 20h, 2 S)
Operations Research
• Thorough operational research: modelling and business application (2 ECTS, 21h, 1 S)
• Game theory (1 ECTS, 10h, 1 S)
• Forecasting models (2 ECTS, 20h, 1 S)
• Constraint programming (2 ECTS, 20h, 2 S)
• Multi-objective and multi-criteria optimisation (2 ECTS, 20h, 2 S)
• SAS OR (2 ECTS, 20h, 2 S)
Research Initiation Initiative
• Scientific Paper review (1 ECTS, 10h, 1 S)
• Final research project on BIG DATA (2 ECTS, 39, 2 S)
BI Architecture
• BI Theory (2 ECTS, 20h, 2 S)
• BI Practice (2 ECTS, 20h, 2 S)
Languages and workshops (4 ECTS, 105h, 1&2 S)
• French as a Foreign language
• CV workshop
• Personal and Professional Project
Internship
• Internship (9 ECTS, 22 weeks minimum)
Thesis
• Master thesis (9 ECTS, 150h)

Teaching

Fourteen external teachers (lecturers from universities, teacher-researchers, professors etc.), supported by a piloting committee, will bring together the training given in Cergy.

All the classes will be taught in English, with the exception of:
• The class of FLE (French as a foreign language), where the objective is to teach the students how to understand and express themselves in French.
• Cultural Openness, where the objective is to enrich the students’ knowledge of French culture.
The EISTI offers an e-learning site to all its students, which complements everything the students will learn through their presence and participation in class:
• class documents, practical work and tutorials online
• questions and discussions between teachers and students, and among students
• a possibility of handing work in online

All Master’s students are equipped with a laptop for the duration of the program that remains the property of the EISTI.

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During this programme, students study, employ and reflect on the principles underpinning computer science. The programme is designed for individuals wishing to pursue careers as computer science professionals. Read more
During this programme, students study, employ and reflect on the principles underpinning computer science. The programme is designed for individuals wishing to pursue careers as computer science professionals.

From organisational culture and human-computer interaction to web services and distributed computing on virtualised and cloud based systems, this programme leads students to reflect on the choice of methods and tools. It will provide practical experience in the analysis and understanding of problems, systems and structures through the study of realistic case studies. The student will be equipped to deal with the intense demands of modern software development, critically evaluate and employ appropriate concepts and principles to build solutions of commercial, industrial or research value.

Students may choose options focusing on cyber security and forensics, data warehousing and business intelligence or user-centered web engineering and software engineering management.

Through our short course centre opportunity may also be provided to study for the following professional qualifications: Microsoft Technology Associate Exams; Certified Professional Java SE Programmer; Java Certified Associate; Oracle Certified Associate (OCA).

The availability of some courses is subject to satisfying constraints that may come into effect in the year of entry.

Visit the website http://www2.gre.ac.uk/study/courses/pg/com/cgcs

Computing - General

Come and study in the award-winning Department of Computing & Information Systems on the magnificent Greenwich Campus. Welcoming home and international students from all backgrounds, CIS provides an exciting, diverse and friendly environment in which to study.

The latest university league table published in the Sunday Times, has rated the computer science department as seventh in the UK for teaching excellence.

What you'll study

Full time
- Year 1:
Students are required to study the following compulsory courses.

PG Project (SST) (60 credits)
Systems Development Management and Governance (15 credits)
Enterprise Software Engineering Development (15 credits)
Enterprise Patterns and Frameworks (15 credits)
Programming Enterprise Components (15 credits)
Clouds, Grids and Virtualisation (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

Students are required to choose 15 credits from this list of options.

Mobile Application Development (15 credits)
User Centred Web Engineering (15 credits)
Big Data (15 credits)

Students are required to choose 30 credits from this list of options.

Audit and Security (15 credits)
Data Warehousing (15 credits)
Enterprise Web Programming (15 credits)
Computer Crime and Forensics (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)

Part time
- Year 1:
Students are required to study the following compulsory courses.

Systems Development Management and Governance (15 credits)
Programming Enterprise Components (15 credits)
Essential Professional and Academic Skills for Masters Students
English Language Support Course (for Postgraduate Students in the School of Computing and Mathematical Sciences)

Students are required to choose 30 credits from this list of options.

Enterprise Software Engineering Development (15 credits)
Enterprise Patterns and Frameworks (15 credits)
Clouds, Grids and Virtualisation (15 credits)

- Year 2:
Students are required to study the following compulsory courses.

PG Project (SST) (60 credits)

Students are required to choose 15 credits from this list of options.

Enterprise Software Engineering Development (15 credits)
Enterprise Patterns and Frameworks (15 credits)
Clouds, Grids and Virtualisation (15 credits)

Students are required to choose 15 credits from this list of options.

Mobile Application Development (15 credits)
Data Warehousing (15 credits)
User Centred Web Engineering (15 credits)
Big Data (15 credits)

Students are required to choose 30 credits from this list of options.

Audit and Security (15 credits)
Enterprise Web Programming (15 credits)
Computer Crime and Forensics (15 credits)
Business Intelligence and Data Mining (15 credits)
Enterprise Systems Integration (15 credits)

Fees and finance

Your time at university should be enjoyable and rewarding, and it is important that it is not spoilt by unnecessary financial worries. We recommend that you spend time planning your finances, both before coming to university and while you are here. We can offer advice on living costs and budgeting, as well as on awards, allowances and loans.

Assessment

Students are assessed through examinations, coursework and a project.

Professional recognition

This programme is accredited by the British Computer Society (BCS). On successful graduation from this degree, the student will have fulfilled the academic requirement for registration as a Chartered IT Professional (CITP) and partially fulfilled the education requirement for registration as a Chartered Engineer (CEng) or Chartered Scientist (CSci). For a full Chartered status there are additional requirements, including work experience. Please contact the BCS for further information. The programme also has accreditation from the European Quality Assurance Network for Informatics Education (EQANIE).

Career options

Graduates from this programme are equipped for employment in industry, commerce or education with a proficiency in the key theoretical and practical areas in computer science, including their application to modern software systems development.

Find out how to apply here - http://www2.gre.ac.uk/study/apply

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