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Masters Degrees (Semantic Web)

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The programme intends to develop your competence in using tools and techniques for producing computer systems solutions from a sound mathematical and scientific base while appreciating the professional responsibilities and quality needed by industry. Read more
The programme intends to develop your competence in using tools and techniques for producing computer systems solutions from a sound mathematical and scientific base while appreciating the professional responsibilities and quality needed by industry.

What's covered in the course?

The course is designed to cover the advanced concepts of computer science in the first semester, including service-oriented architecture, advanced HCI techniques and advanced mobile computing.

In your second semester, you will consolidate your first semester learning by studying further advanced subjects that emphasise Semantic Web technologies, advanced data science, and Research and Project Management. In addition, you will complete an individual project that provides opportunity to demonstrate technical and general employability skills in preparation for career progression. More specifically, the individual project simulates typical graduate workplace tasks that require in-depth knowledge and skills in a specific area of computer science. This will include consideration of wider issues and the ability to manage activities and resources, as well as generate, implement and report on solutions to meet task objectives.

Throughout your studies, you’ll be supported by our expert teaching staff, all of whom have a wide range of research and industrial experience in areas such as intelligent systems, mobile computing, Semantic Web, machine learning and software engineering, which they use to enhance the curriculum.

Why choose us?

-You’ll have access to dedicated industry-standard facilities in our own fully equipped laboratory. Based within our £114 million Millennium Point building, you’ll be able to undertake work such as artificial intelligence, human computer interaction, mobile and web application development, and data science.
-We are home to a Cisco Systems and a Microsoft Academy Centre – one of Microsoft’s top UK university-based academies – and we are a member of the Microsoft Developer Network Academic Alliance. We are also a Cisco ASC (Academy Support Centre) and Cisco Instructor Training Centre (ITC) – one of only 10 such instructor training centres in the UK.
-The course is supported through the activities of the Innovations in Computing Education research group, designed to keep teaching and assessment updated to match international trends.
-We have strong links with companies such as Oracle, LPI, Microsoft, AWS and Apple, which ensure that the course is relevant and respected by employers.

Course in depth

Knowledge and understanding are acquired though a mixture of formal lectures, tutor-led seminars and practical activities, with other independent learning activities at all stages.

Emphasis is placed on guided, self-directed and student-centred learning with increasing independence of approach, thought and process.

The course provides access to effective commercial development environments and ensures students have practical awareness of computer systems requirements. You are required to meet strict deadlines, and to manage and plan overall workload.

Knowledge is assessed formatively and summatively, by a number of methods, including seminars, course-work, viva, presentation, and project work.

Assessment criteria are published both at a generic course level and to provide guidance for individual items of assessment.

You will undertake a major project involving research and application of that research in the solution of appropriate systems problems.

Semester One
-Service-Oriented Architecture (SOA) 20 credits
-Advanced Mobile Computing 20 credits
-Advanced HCI 20 credits

Semester Two
-Research Methods and Project Management 20 credits
-Advanced Data Science 20 credits
-Semantic Web and Knowledge Engineering 20 credits

Semester Three
-Master’s Project 60 credits

Enhancing your employability skills

We know that employers are looking for graduates who have a good balance between in-depth academic knowledge and technical and practical expertise, which is why our course is geared towards employability.

What you learn on our course will help you to stand out when you look for your first professional role.Because you’ll know how to use sophisticated, industry-standard software, you will be able to demonstrate that you can put into practice your deep theoretical knowledge.

We will also prepare you for a career by equipping you with a range of transferable skills, such as complex problem-solving expertise, the ability to analyse in a careful and considered manner, and working as a team member.

In addition, our specialist industry links with the Linux Professional Institute, the Oracle Academy, Cisco, and Microsoft, plus our world-class facilities, will mark you out as a highly employable graduate.

This is why our graduates have gone on to pursue computing and software development and designer careers in a wide range of industries, from SME software companies, to industry, government, banking and healthcare. Furthermore, many graduates continue their studies to Doctorate level.

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The Digital Media, Culture and Education MA explores the theory and practice of media education and emergent new literacies in the digital age. Read more
The Digital Media, Culture and Education MA explores the theory and practice of media education and emergent new literacies in the digital age. The programme combines theory with practical opportunities for media production. Students will critically examine new developments within digital media and work with partners including the British Film Institute (BFI).

Degree information

This programme provides the opportunity to explore media education, media literacy and related fields. It combines theory with practical opportunities in moving image production, Internet cultures and game design. Students will critically examine developments in the fields of new media, including the impact of new technologies on education, and debates about the place and purpose of media in society.

Students undertake modules to the value of 180 credits. The programme consists of two core modules (60 credits), two optional modules (60 credits), a dissertation (60 credits) or a report (30 credits) and an additional optional module (30 credits).

Core modules
-Digital Media, Cultural Theory and Education
-Internet Cultures: Theory & Practice

Recommended optional modules include:
-Moving Image Production
-Digital Games, Play and Creativity

Dissertation/report
All students undertake an independent research project, which culminates in a dissertation of 20,000 words or a report of 10,000 words.

Teaching and learning
Teaching is delivered by face-to-face lectures and seminars, practical workshops combined with online-learning. Students are assessed by coursework assignments of up to 5,000 words, plus practical work for some modules, and a 20,000-word dissertation or 10,000-word report.

Careers

Graduates of this programme are currently working across a broad range of areas. Some are working as teachers in primary, secondary schools and further and higher education, while others have jobs as within areas related to digital media. Graduates can also be found working as museum and gallery education officers and in other informal learning spaces.

Why study this degree at UCL?

This programme is run by UCL's London Knowledge Lab (LKL) where collaborating computer and social scientists research the future of learning with digital technologies in a wide range of settings. LKL conducts research, design and development across a broad range of media, systems and environments and brings together computer and social scientists from the areas of education, sociology, culture and media, semiotics, computational intelligence, information management, personalisation, semantic web and ubiquitous technologies.

Students are able to work with the BFI, our partner for one of our modules, as well as leading researchers from the DARE Collaborative, a research partnership focussed on the digital arts in education led by UCL Institute of Education (IOE) and the BFI.

LKL conducts research, design and development across a broad range of media, systems and environments and brings together computer and social scientists from the areas of education, sociology, culture and media, semiotics, computational intelligence, information management, personalisation, semantic web and ubiquitous technologies.

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Our Master's programmes seek to develop knowledge, creativity and originality in one package - you. Each programme is a framework to help you to develop. Read more
Our Master's programmes seek to develop knowledge, creativity and originality in one package - you. Each programme is a framework to help you to develop:
a systematic understanding of knowledge;
a comprehensive understanding of techniques relevant to your area of study;
the key skills associated with critical awareness and evaluation.

As part of your development on the course, you will be increasingly expected to demonstrate that you can deal with complex issues in a systematic and creative manner and demonstrate self-direction and originality in problem solving.

Your studies on the course will cover:

Research Methods

This module will introduce methods of data collection and analysis when conducting empirical research. This research can take place in an organisational setting. Both in the private or the public sector. This module is essential preparation for the dissertation.

Enterprise Modelling

Cultivates skills and knowledge related to business, conceptual and software modelling. Example topics of study include different paradigms for modelling (including business services, processes and objects), techniques for modelling the business domain and business behaviour, the relationship between business modelling and software modelling and the use of the Unified Modelling Language (UML).

ERP Systems Theory and Practice

Examines the rationale, theories and practices around Enterprise Resource Planning systems (ERP) and develops the knowledge required to understand the forces driving ERP design and implementation. Example topics of study include enterprise systems strategy and rationale, issues of organisational implementation and business services, processes and functions from an ERP perspective. The module provides an introduction to the SAP R/3 environment and the practice of business process integration in that environment.

ERP Systems Deployment and Configuration

Examines the implications of implementing ERP systems in organisations and develops the key skills necessary to deploy and configure ERP systems. Example topics of study include business process improvement alongside enterprise systems configuration and configuration management (including Master Data Management, business services, processes and functions). The module examines practical aspects of configuration in the context of the SAP R/3 environment.

Service-oriented Architecture

Examines the organisational impact of service-oriented approaches and the technologies necessary for the successful implementation of enterprise and web services. Example topics of study include issues in creating and managing a system landscape based on services, architectural approaches to service-orientation and web service technologies (including semantic web services). Practical aspects of web service implementation are examined in the context of integration via the SAP Netweaver environment.

Data Management and Business Intelligence

Develops the knowledge and skills necessary to support the development of business intelligence solutions in modern organisational environments. Example topics of study include issues in data/information/knowledge management, approaches to information integration and business analytics. Practical aspects of the subject are examined in the context of the SAP Netweaver and Business Warehouse environment.

Systems project management

Develops a critical awareness of the central issues and challenges in information systems project management. Example topics of study include traditional project management techniques and approaches, the relations between projects and business strategy, the role and assumptions underpinning traditional approaches and the ways in which the state-of-the-art can be improved.

Semantic Integration Frameworks

Helps you develop a critical and practical understanding of concepts, standards and frameworks supporting semantic system integration, with a particular emphasis on the Semantic Web – the web of the future. Example topics of study include ontologies and their uses, ontology management and integration, inferencing and reasoning for and in semantic integration, as well as semantic integration standards such as RDF and OWL.

Dissertation

In addition, provided that you have reached an acceptable standard in the assessments and examinations, you may then undertake a dissertation. Work on a dissertation for this course will normally involve an in-depth study in the area of distributed information systems and computing (eg, a state-of-the-art review together with appropriate software development) and provides you with an excellent opportunity to demonstrate your expertise in this area to future employers or as a basis for future PhD study. Additionally, you can now work on an internship during your dissertation (see Special Features below).

Awards

A master's degree is awarded if you reach the necessary standard on the taught part of the course and submit a dissertation of the required standard. If you do not achieve the standard required, you may be awarded a postgraduate diploma or postgraduate certificate if eligible.

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This Masters programme trains graduates of engineering, science or related disciplines in general and specialist process systems engineering subjects. Read more

This Masters programme trains graduates of engineering, science or related disciplines in general and specialist process systems engineering subjects.

Such areas are not generally covered in engineering and science curricula, and BSc graduates tend to be ill prepared for the systems challenges they will face in industry or academia on graduation.

Programme structure

This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. It consists of eight taught modules and a dissertation.

Example module listing

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

Facilities, equipment and academic support

Modules related to the different groups are taught by a total of six full-time members of staff and a number of visiting lecturers.

As part of their learning experience, students have at their disposal a wide range of relevant software needed to support the programme material dissertation projects. In recent years, this work included the design of various knowledge-based and business systems on the internet, the application of optimisation algorithms, and semantic web applications.

Numerous laboratory facilities across the Faculty and the University are also available for those opting for technology-based projects, such as the process engineering facility, a control and robotics facility and signal processing labs.

The work related to the MSc dissertation can often be carried out in parallel with, and in support of, ongoing research. In the past, several graduates have carried on their MSc research to a PhD programme.

Career prospects

Engineers and scientists are increasingly expected to have skills in information systems engineering and decision-support systems alongside their main technical and/or scientific expertise.

Graduates of this programme will be well prepared to help technology-intensive organisations make important decisions in view of vast amounts of information by adopting, combining, implementing and executing the right technologies.

Educational aims of the programme

The programme aims to provide a highly vocational education which is intellectually rigorous and up-to-date. It also aims to provide the students with the necessary skills required for a successful career in the process industries.

This is achieved through a balanced curriculum with a core of process systems engineering modules supplemented by a flexible element by way of elective modules that permit students to pursue an element of specialisation relevant to their backgrounds, interests and/or career aspirations.

An integrated approach is taken so as to provide a coherent view that explores the interrelationships between the various components of the programme. The programme draws on the stimulus of the Faculty’s research activities.

The programme provides the students with the basis for developing their own approach to learning and personal development.

Programme learning outcomes

Knowledge and understanding

  • State-of- the-art knowledge in process systems engineering methods, in the areas of: modelling and simulation of process systems, mathematical optimization and decision making, process systems design, supply chain management, process and energy integration, and advanced process control technologies
  • Advanced level of understanding in technical topics of preference, in one or more of the following aspects: renewable energy technologies, refinery and petrochemical processes, biomass processing technologies, and knowledge-based systems

Intellectual / cognitive skills

The programme aims to strengthen cognitive skills of the students, particularly in the aspects of problem definition, knowledge and information acquiring, synthesis, and creativity, as collectively demonstrable through the successful completion of the research dissertation. The key learning outcomes include the abilities to:

  • Select, define and focus upon an issue at an appropriate level
  • Collect and digest knowledge and information selectively and independently to support a particular scientific or engineering enquiry
  • Develop and apply relevant and sound methodologies for analysing the issue, developing solutions, recommendations and logical conclusions, and for evaluating the results of own or other’s work

Professional practical skills

The programme primarily aims to develop skills for applying appropriate methods to analyse, develop, and assess process systems and technologies. The key learning outcomes include the abilities to:

  • Assess the available systems in the process industries
  • Design and/or select appropriate system components, and optimise and evaluate system design
  • Apply generic systems engineering methods such as modelling, simulation, and optimization to facilitate the assessment and development of advanced process technologies and systems

Key / transferable skills

The programme aims to strengthen a range of transferable skills which are relevant to the needs of existing and future professionals in knowledge intensive industries irrespective of their sector of operation. The key learning outcomes include the further development of the skills in the following areas:

  • Preparation and delivery of communication and presentation
  • Report and essay writing
  • Use of general and professional computing tools
  • Collaborative working with team members
  • Organising and planning of work
  • Research into new areas, particularly in the aspect of literature review and skills acquisition

Global opportunities

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

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



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The impact of Information Systems on everyday life continually expands at a monumental rate. Computing is increasingly embedded in everything we use from; transport, financial and telecommunications systems to everyday personal items such as toothbrushes and running shoes. Read more
The impact of Information Systems on everyday life continually expands at a monumental rate. Computing is increasingly embedded in everything we use from; transport, financial and telecommunications systems to everyday personal items such as toothbrushes and running shoes. The pervasive nature of computing coupled with the ever increasing demand for improved products and services drives the discovery of innovative solutions through the use of information systems. This has led to a critical dependence emerging between computing and practically all industries.

Graduates and engineers who are able to fully exploit the potential that computing and information systems offer within a range industries including, Retail, Manufacturing, Health, and Communications; are highly sought after. If you are looking to further your employment options in your current industry, but have little or no technical experience, then this programme is for you.

* This programme is suited to students from a non-IT background or with little prior technical experience who want to further enhance or or change career focus, to widen employment opportunities in a vast selection of computing related industries and sectors.
* Designed for non-IT professionals who want to develop a firm technical foundation in the latest industry relevant programming languages and software development techniqus (agile, which can open up more technical and senior level positions in their current industry.
* Guided by academics with an extensive spectrum of industrial experience, the programme introduces you to the core aspects of computing and allows you to choose from a variety of optional specialist modules, such as Mobile Devices and Social Networks, Business Technology Strategy and Graphical User Interface design, developing both your practical and theoretical skills.
* The core modules introduce aspects of computing, including a double module in object-oriented programming (using Java) and a double module in information systems.
* These core modules are supplemented by optional specialist modules covering a broad range of subjects relevant to the software industry, such as Network Planning, Finance and Management, Entrepreneurship in Information Technology and Decision and Risk.
* Your project work will typically involve the design and implementation of a significant piece of software within your chosen specialism. Projects undertaken for external organisations focusing on an industrial or commercial application encouraged.
* You will learn about and develop extensive technical knowledge of the latest developments in new languages and tools for web systems (XML, Advanced databases, Semantic web).
* This intensive one year programme is aimed at students without a background in Computer Science � it is a conversion course for those who want a career in computing.

Why study with us?

Queen Mary has a prestigious history in computing and electronic engineering, we had one of the first Computer Science Departments in the country, and The School of Electronic Engineering and Computer Science is rated in the top 20 universities in the UK for studying computer science and electronic engineering.

The best things I have found about the course have been the breadth of content available and the quality of teaching.
Anuruddha Jaithirtha

* This programme is available part-time
* It permits students to follow a technical or business focus
* There is a wide range of employment-relevant module choices
* Early coverage of Networks in core modules
* There are lectures and laboratories specific to students on this programme, a number of modules have invited talks from commercial and other organisations
* Up-to-date modules in real-time and critical systems, functional programming and security, intelligent and multi-agent systems (such as Siri), and web-based document databases

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IN BRIEF. MSc by project accredited by the British Computer Society. Gain hands-on experience of the design and implementation of databases and web applications. Read more

IN BRIEF:

  • MSc by project accredited by the British Computer Society
  • Gain hands-on experience of the design and implementation of databases and web applications
  • Learn data-mining techniques using popular tools in different application domains
  • Part-time study option
  • International students can apply

COURSE SUMMARY

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.

COURSE 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.

TEACHING

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.

ASSESSMENT

  • Coursework 60%
  • Examinations 40%

EMPLOYABILITY

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.

LINKS WITH INDUSTRY

Our links with industry include large companies (BT, Oracle, Microsoft) and local companies.

These companies engage with the University by giving guest seminars and often our students will work with them on their MSc Project.

FURTHER STUDY

Many of our graduates will go on to further study in our Computer Networks and Telecommunications Research Centre (CNTR)

The CNTR undertakes both pure and applied research in the general field of telecommunications and computer networking including computer networking technologies, wireless systems, networked multimedia applications, quality of service, mobile networking, intelligent buildings, context driven information systems and communication protocols. Much of this work is funded through research grants and supported by industry. In addition, members of the group are actively involved in a range of public engagement courses which aim to raise the awareness of these subjects for the general public and in schools.

Research themes in this Centre include:

  • Wireless technologies and sensor networks
  • Context and location based information systems
  • Intelligent buildings and energy monitoring
  • Communication protocols, traffic routing and quality of service
  • Network planning, traffic modelling and optimisation
  • Ubiquitous and ambient technology
  • Information security and computer forensics
  • Public Awareness


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You will study in an innovative department with an international reputation for research, training and education in software engineering, with access to facilities and expertise from the Software Technology Research Laboratory (STRL). Read more

About the course

You will study in an innovative department with an international reputation for research, training and education in software engineering, with access to facilities and expertise from the Software Technology Research Laboratory (STRL). Taught by acknowledged experts from the STRL, Software Engineering will equip you with skills you need for industry.

Accredited by the European-wide accreditation system for Informatics curricula, the course is committed to excellence in European-wide software education and training of engineers to deliver high-quality and trustworthy software systems that meet industrial needs. The taught element of the course lasts for the first two semesters, while the third semester is devoted to the project. The total length of study depends on the mode of delivery. .

Reasons to Study

• Gain an industry-recognised accreditation
the course is accredited by the British Computer Society (BCS) to Chartered Engineering (CEng) level

• Taught by expert academic staff
taught by experienced experts within the Software Technology Research Laboratory (STRL) with international reputation for research, training and education in software engineering, with access to specialist facilities

• Specialise your learning to your area of interest
combine modules from across Cyber Security, Cyber Technology, Digital Forensics and Software Engineering, allowing you to tailor the course to your areas of interest

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

• Benefit from our Research Expertise
our internationally recognised Software Technology Research Laboratory (STRL) will have input into the course and will explore and allow you to understand the current research issues

• Excellent career prospects
graduates have gone on to work in both public and private sector organisations, and have been employed in positions in consultancies and worked for companies including IBM, Deloitte, Airbus and BT

Course Structure

First semester:

• Research Methods
• Advanced Requirements Engineering
• Software Project Management and Testing
• Pervasive Systems

Second Semester:

• Software Evolution
• Formal Methods Engineering
• Software Engineering for Dependable Systems
• Advanced Topics in Software Engineering

Project:
Your project will be chosen to explore an issue from a wide range of applications such as:

• Electronic Purse
• Electronic Patient Records
• Personal Insulin Pump Systems
• London Ambulance System
• System of Human Resources
• E-voting System
• Arion 5 Launcher
• Flight Control System

Optional Placement

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

Teaching and assessment

There are provisions for a traditional classroom-based delivery, either part-time or full-time, as well as distance learning. Teaching will include formal lectures, tutorials and labs. You will also be expected to undertake independent study and research to support your assignments and dissertation. Assessment will be 100 per cent coursework. It will involve various group and individual methods, including oral exams, projects, presentations, written essays and reports.

Contact and learning hours

The time allocated to study is around 30 hours per week, carried out in block teaching. The taught element of the course lasts for the first two semesters, while the third semester is devoted to the project.

Academic expertise

he Software Technology Research Laboratory is one of the largest software engineering research groups in the UK and its research activities are acknowledged as being at the highest level of international excellence. In the last UK HEFCE Research Assessment Exercise (RAE 2008), 85 per cent of the research produced by the group was considered to be world-leading, internationally excellent or international.

The major themes within the lab include computer security and trust, software evolution, theory and computational paradigms and semantic web and service oriented computing. The staff working in these areas bring to the course their academic excellence and their experience of applying their work to various industrial sectors.

To find out more

To learn more about this course and DMU, visit our website:
Postgraduate open days: http://www.dmu.ac.uk/study/postgraduate-study/open-evenings/postgraduate-open-days.aspx

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

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

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Efficient management of data and knowledge are key factors not only to the success of almost any enterprise, but also to the successful handling of today's vast amounts of science related data. Read more
Efficient management of data and knowledge are key factors not only to the success of almost any enterprise, but also to the successful handling of today's vast amounts of science related data: with the transition to the information age and the knowledge economy, data has become both increasingly central and critical to all activities. For example, imagine the huge amounts of genomic or patient data available electronically, and how the quality of their management can affect society.

The Data and Knowledge Management pathway allows students to take specialist themes concerned with methods and technologies for the adequate management of data and knowledge. The Managing Data theme focuses on the design, maintenance, and query processing of both structured and unstructured databases. The Learning from Data theme covers principles, algorithms, and technologies underlying machine learning, probabilistic modelling, and optimisation, while exposing students to relevant applications. The Advanced Web Technologies theme provides students with a deep understanding of the technologies that are being used to support the continuing evolution of the Web, including Semantic 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 students
-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

Career opportunities

Students following the Data and Knowlege Management pathway have all the career choices and options as described for general Advanced Computer Science.

In addition, students of this pathway are ideally placed to work in positions requiring an understanding of modern data and knowledge management tools and technologies. This includes data and knowledge engineering positions in all areas where data is stored and managed electronically, i.e., in all areas, including the finance, retail, and healthcare sector.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with CEng accredited Bachelors programme.

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Semantic Technologies is a relatively new term that describes all areas concerned with using and developing software and methodologies for meaning-centred manipulation of information. Read more
Semantic Technologies is a relatively new term that describes all areas concerned with using and developing software and methodologies for meaning-centred manipulation of information. The aim is to provide software and methodologies so that web resources, data in databases and raw data associated with programs can be processed and manipulated in a more intelligent way. This requires storing, understanding, manipulating and reasoning about the meaning of the data. Semantic technologies are increasingly being used in such varied applications as the semantic web, health care and biomedical domains, the life sciences, software/hardware industries and the automotive industry.

The Semantic Technologies pathway combines themes such as 'Data on the Web' with 'Ontology Engineering and Automated Reasoning'. These core offerings can be combined with any other theme. Good complementary themes are Data Engineering, Managing Data, Learning from Data, Security and Software Engineering.

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 students
-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

Career opportunities

Students following the Semantic Technologies pathway have all the career choices and options as described for general Advanced Computer Science.

In addition, students of this pathway are ideally placed to work in software companies or for healthcare providers who are using or developing Semantic Technologies.

We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry.

Accrediting organisations

This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with a CEng accredited Bachelors programme.

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Created in the context of the rapid advancement of the renewable-energy industry, this Masters programme investigates both renewable energy and systems technologies. Read more

Created in the context of the rapid advancement of the renewable-energy industry, this Masters programme investigates both renewable energy and systems technologies.

It is designed to build your competence and confidence in the R&D and engineering tasks that are demanded of scientific engineers in the renewable and sustainable-development sector.

Programme structure

This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. It consists of eight taught modules and a dissertation.

Example module listing

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

Facilities, equipment and academic support

Modules related to the different groups are taught by a total of six full-time members of staff and a number of visiting lecturers.

As part of their learning experience, students have at their disposal a wide range of relevant software needed to support the programme material dissertation projects. In recent years, this work included the design of various knowledge-based and business systems on the internet, the application of optimisation algorithms, and semantic web applications.

Numerous laboratory facilities across the Faculty and the University are also available for those opting for technology-based projects, such as the process engineering facility, a control and robotics facility and signal processing labs.

The work related to the MSc dissertation can often be carried out in parallel with, and in support of, ongoing research. In the past, several graduates have carried on their MSc research to a PhD programme.

Career prospects

Engineers and scientists are increasingly expected to have skills in information systems engineering and decision-support systems alongside their main technical and/or scientific expertise.

Graduates of this programme will be well prepared to help technology-intensive organisations make important decisions in view of vast amounts of information by adopting, combining, implementing and executing the right technologies.

Educational aims of the programme

This programme investigates both renewable energy and systems technologies in order to produce scientific researchers and engineers who are competent in the R&D and engineering tasks applicable to the renewable energy and sustainable development sectors.

Its primary aims lie in developing a global understanding of the major types of renewable energy technologies, in-depth knowledge of the technology for biomass-based renewable energy, and knowledge and skills in systems modelling and optimisation.

A balanced curriculum will be provided with a core of renewable energy and systems engineering modules supplemented by a flexible element by way of elective modules that permit students to pursue an element of specialisation relevant to their backgrounds, interests and/or career aspirations.

An integrated approach is taken so as to provide a coherent view that explores the interrelationships between the various components of the programme.

Programme learning outcomes

Knowledge and understanding

The programme aims to develop the knowledge and understanding in both renewable energy and systems engineering. The key learning outcomes include:

  • State-of- the-art knowledge in renewable energy technologies, in terms of: the sources, technologies, systems, performance, and applications of all the major types of renewable energy; approaches to the assessment of renewable energy technologies; the processes, equipment, products, and integration opportunities of biomass-based manufacturing
  • State-of- the-art knowledge in process systems engineering methods, in the areas of: modelling and simulation of process systems; mathematical optimization and decision making; process systems design
  • Advanced level of understanding in technical topics of preference, in one or more of the following aspects: process and energy integration, economics of the energy sector, sustainable development, supply chain management

Intellectual / cognitive skills

The programme aims to strengthen cognitive skills of the students, particularly in the aspects of problem definition, knowledge and information acquiring, synthesis, and creativity, as collectively demonstrable through the successful completion of the research dissertation. The key learning outcomes include the abilities to:

  • Select, define and focus upon an issue at an appropriate level
  • Collect and digest knowledge and information selectively and independently to support a particular scientific or engineering enquiry
  • Develop and apply relevant and sound methodologies for analysing the issue, developing solutions, recommendations and logical conclusions, and for evaluating the results of own or other’s work

Professional practical skills

The programme primarily aims to develop skills for applying appropriate methods to analyze, develop, and assess renewable technologies and systems. The key learning outcomes include the abilities to:

  • Assess the available renewable energy systems
  • Design and select appropriate collection and storage, and optimise and evaluate system design
  • Apply generic systems engineering methods such as modelling, simulation, and optimization to facilitate the assessment and development of renewable energy technologies and systems

Key / transferable skills

The programme aims to strengthen a range of transferable skills which are relevant to the needs of existing and future professionals in knowledge intensive industries irrespective of their sector of operation. The key learning outcomes include the further development of the skills in the following areas:

  • Preparation and delivery of communication and presentation
  • Report and essay writing
  • Use of general and professional computing tools
  • Collaborative working with team members
  • Organizing and planning of work
  • Research into new areas, particularly in the aspect of literature review and skills acquisition

Global opportunities

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

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



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This MSc programme offers a broad range of advanced study options, with modules taken from a variety of application areas. It is multidisciplinary and, in addition to computer science, you may choose options in which computer science intersects with other fields. Read more
This MSc programme offers a broad range of advanced study options, with modules taken from a variety of application areas. It is multidisciplinary and, in addition to computer science, you may choose options in which computer science intersects with other fields. The programme prepares you for a wide range of careers depending on your selection of modules studied. Typical jobs after graduation include advanced programmer, software development and support, software engineer, product designer/developer, systems analyst, interface/interaction designer, database developer, and other specialist employment based on your selected study areas.

Programme outline

Modules can include:

Introduction to Computer Vision
XML and Structured Documents
Advanced Program Design
Machine Learning
Design for Human Interaction
Program Specifications
Advanced Database Systems & Technology
Distributed Systems and Security
Introduction to Law for Science and Engineering

Techniques for Computer Vision
The Semantic Web
Information Retrieval
Mobile Services
Security and Authentication
Real Time & Critical Systems
Business Technology Strategy
Interactive Systems Design
Software Analysis and Verification
Software Risk Assessment
C++ for Image Processing


Please note that module availability is subject to change.

Recent graduate destinations

* Support Engineer, Computer Assets
* Analyst, Credit Suisse First Boston
* Business Analyst, Norton Rose
* Queen Mary, University of London
* Tesco Plc
* The Open University

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This MSc programme focuses on advanced theoretical and practical techniques in program design, and the management of software project risk. Read more
This MSc programme focuses on advanced theoretical and practical techniques in program design, and the management of software project risk. It includes training in vital areas such as security, specification, risk management, usability, and design integrity.

You will learn advanced techniques in program design (including software patterns and component technologies) and information handling (structured information, databases). You can study key issues of interactive system design, leading to the ability to identify issues and trade-offs in the design of human-computer interaction, and to invent and evaluate alternative solutions to design problems. You will gain knowledge in the mathematical foundations of software and the practical application of these techniques. You will develop skills to manage software project risks and learn about the development of tools to support decision-making.

The programme will enable you to become competitive in the most technically oriented branches of software engineering. Typical jobs after graduation include software risk analyst, system designer, software quality assurance, software engineer, programmer, usability consultant, systems analyst, and software architect.
Programme outline

Central modules can include:
Design for Human Interaction
Functional Programming
Program Specifications
Real Time & Critical Systems
Software Analysis and Verification
Software Risk Assessment
MSc Project

Further options can include:
Machine Learning
XML and Structured Documents
Advanced Program Design
Advanced Database Systems & Technology
Distributed Systems and Security
Mobile Services
Security and Authentication
Business Technology Strategy
Interactive Systems Design
The Semantic Web
High Performance Computing

Please note that module availability is subject to change.

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Explore advanced topics in computer science with this wide-ranging programme, which will equip you with the understanding and practical skills to succeed in a variety of careers. Read more

Explore advanced topics in computer science with this wide-ranging programme, which will equip you with the understanding and practical skills to succeed in a variety of careers.

Rooted in the established research strengths of the School of Computing, the programme will introduce topics like systems programming and algorithms before allowing you to specialise through your choice of modules.

You could look at emerging approaches to human interaction with computational systems, novel architectures such as clouds, or the rigorous engineering needed to develop cutting-edge applications such as large-scale data mining and social networks.

Building on your existing knowledge of computer science, you’ll develop the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology. 

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as cloud computing, image analysis, machine learning, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Foundations of Modelling and Rendering 15 credits
  • Games Engines and Workflow 15 credits
  • Geometric Processing 15 credits
  • High-Performance Graphics 15 credits
  • Animation and Simulation 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science students have included:

  • iPad interaction for wall-sized displays
  • Modelling the effects of feature-based attention in the visual cortex
  • Relevance and trust in social computing for decision making
  • Energy-efficient cloud computing
  • Smart personal assistant - Ontology-enriched access to digital repositories

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science. Read more

Developments in cloud computing technology are transforming the way we live and work. This programme will equip you with specialist knowledge in this fast-growing field and allow you to explore a range of advanced topics in computer science.

You’ll gain a foundation in topics like systems programming and algorithms, as well as specialist modules in advanced distributed systems – especially cloud techniques, technologies and applications.

Building on your existing knowledge of computer science, you’ll also choose from optional modules in topics across computer science. You could look at emerging approaches to human interaction with computational systems, data mining and functional programming among others.

The programme will give you the theoretical and practical skills required to design and implement larger, more complex systems using state-of-the-art technologies. You’ll even have the chance to work as an integral member of one of our research groups when you develop your main project.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming. Throughout the year you’ll also take modules developing your understanding of cloud computing itself, from designing the high-level framework of a distributed system to big data and the “internet of things”.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, machine learning, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Cloud Computing) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • MSc Project 60 credits
  • Cloud Computing 15 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Machine Learning 10 credits
  • Information Visualization 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Data Mining and Text Analytics 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science (Cloud Computing) students have included:

  • Intelligent services to support sensemaking
  • Google cloud data analysis
  • Hadoop for large image management
  • Evaluating web service agreement in a cloud environment

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science. Read more

Big data is becoming more and more important in fields from science to marketing, engineering medicine and government. This programme will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science.

You’ll gain a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like image analysis or text analytics, or broaden your approach with topics like cloud computing.

As one of the few schools with expertise covering text, symbolic and scientific/numerical data analysis, we can provide a breadth of expertise to equip you with a variety of skills – and you’ll work as an integral member of one of our research groups when you develop your main project. We also have close links with the Leeds Institute for Data Analytics which is at the forefront of big data research.

Specialist facilities

You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.

We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.

Course content

Core modules in Semester 1 will lay the foundations of the programme by giving you an understanding of the key topics of algorithms and systems programming, as well as the basic principles of automated reasoning, machine learning and how computers can be made to represent knowledge.

From there you’ll have the chance to tailor your studies to suit your own preferences. You’ll choose from a wide range of optional modules on diverse topics such as image analysis, cloud computing, semantic technologies and developing mobile apps.

Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.

Want to find out more about your modules?

Take a look at the Advanced Computer Science (Data Analytics) module descriptions for more detail on what you will study.

Course structure

Compulsory modules

  • Machine Learning 10 credits
  • Big Data Systems 15 credits
  • Data Science 15 credits
  • MSc Project 60 credits

Optional modules

  • Web Services and Web Data 10 credits
  • Distributed Systems 10 credits
  • Mobile Application Development 10 credits
  • Information Visualization 10 credits
  • User Adaptive Intelligent Systems 10 credits
  • Data Mining and Text Analytics 10 credits
  • Combinatorial Optimisation 10 credits
  • Secure Computing 10 credits
  • Graph Algorithms and Complexity Theory 10 credits
  • Bio-Inspired Computing 15 credits
  • Knowledge Representation and Reasoning 15 credits
  • Algorithms 15 credits
  • Parallel and Concurrent Programming 15 credits
  • Data Mining and Text Analytics 15 credits
  • Cloud Computing 15 credits
  • Semantic Technologies and Applications 15 credits
  • Image Analysis 15 credits
  • Scheduling 15 credits
  • Scientific Computation 15 credits
  • Graph Theory: Structure and Algorithms 15 credits

Learning and teaching

Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.

Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.

Assessment

You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.

Projects

The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.

Recent projects for MSc Advanced Computer Science students have included:

  • Text mining of e-health patient records
  • Java-based visualization on ultra-high resolution displays
  • Data mining of sports performance data
  • Contour topology
  • Efficient computation for simulating tumour growths

A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.

Career opportunities

Computing is an essential component of nearly every daily activity, from the collection, transformation, analysis and dissemination of information in business, through to smart systems embedded in commodity devices, the image processing used in medical diagnosis and the middleware that underpins distributed technologies like cloud computing and the semantic web.

This programme will give you the practical skills to gain entry into many areas of applied computing, working as application developers, system designers and evaluators; but further, links between the taught modules and our research provide our students with added strengths in artificial intelligence, intelligent systems, distributed systems, and the analysis of complex data. As a result, you’ll be well prepared for a range of careers, as well as further research at PhD level.

Graduates have found success in a wide range of careers working as business analysts, software engineers, wed designers and developers, systems engineers, information analysts and app developers. Others have pursued roles in consultancy, finance, marketing and education, or set up their own businesses.



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