Got a love for computing and technology? Hoping to build on the skills you learnt during your undergraduate studies? This essential applied computing masters is well suited to students from a business IT or computing background, helping you to build on existing skills and develop an advanced understanding.
Southampton Solent University’s applied computing masters programme places a unique emphasis on graduate employability, focusing on developing the specific skills that industry employers are seeking.
One of the ways that the course team ensure the curriculum is achieving this goal is through regular consultations with an industry liaison panel. This panel advises the course team on the latest industry developments and the course content is changed accordingly.
These strong links with industry have provided previous School of Media Arts and Technology students with access to a range of work experience opportunities, case studies and guest lectures.
Computing students at Southampton Solent have the opportunity to use industry standard facilities throughout their studies. Our EC Council certified security and networking labs feature a wide variety of equipment from Cisco (including Cisco Packet Tracer), Fluke and HP, as well as high-fidelity simulation systems like the market-leading Opnet. Students also have free access to our devices lab, where they can test their web design projects on a variety of different computing devices.
Students are supported to develop a range of transferable skills throughout the course. These include project management, problem solving and analytical skills that empower students to work in a range of different industries after graduation. Students will also develop high-level academic skills, perfect for those who are hoping to pursue a PhD.
Optional units provide students with the opportunity to specialise in particular areas of computing and business IT – laying the groundwork for a successful career in management, strategic planning or system development.
This master’s course is well-suited to those with a computing or business IT background, and who have either an undergraduate degree or extensive industrial experience in the area. The option choices within the course are ideal for those who wish to focus on a particular niche within computing.
Three optional units from:
Please note: Not all optional units are guaranteed to run each year.
During your studies you will learn to build information systems using a variety of professional-grade software packages. You will also have access to our state-of-the-art IT laboratories; depending on your choice of options you may have access to our specialised network security laboratory or usability lab with eye-tracking facilities.
You’ll have access to our devices lab, a special test area integrated with our existing software development spaces. The devices lab consists of a range of the latest mobile devices mounted on flexible tethers, allowing you to test your websites and apps on real equipment.
Suitable roles for graduates include:
Course content is developed with input from an industrial liaison panel, making sure that your studies include the latest technology and working practice from industry experts.
You’ll also have the chance to work directly with real-world companies on live briefs, events and projects, while regular BCS meetings hosted at the University are your chance to build professional connections and secure valuable work experience opportunities.
Application period/deadline: November 1, 2017 - January 24, 2018
• Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment
• The studies combine both theoretical and practical approach
• Specializations in Applied Computing, Artificial Intelligence, and Computer Egineering
The International Master’s Degree Programme in Computer Science and Engineering (CSE) is a two-year research-oriented programme concentrating on intelligent digital solutions to real world problems. During the past decades, Computer Science and Engineering has had a significant impact into our daily lives. The development continues and soon computers will not be used as separate devices anymore. Instead they will blend into our living environments and offer us rich sets of services through natural and intuitive user interfaces. The graduates from Computer Science and Engineering will play a key role in this development.
The two-year programme has three specialisation options:
• Applied Computing
• Artificial Intelligence
• Computer Engineering
Applied Computing focuses on the next generation of interactive systems that place humans at the focus of the technological development. Adopting a multidisciplinary real-world approach, students have to spend a substantial amount of time working in group projects to develop a variety of systems ranging from interactive online services to games and mobile applications, with a strong focus on innovation and design.
Artificial Intelligence focuses in various fields of AI, such as machine learning, machine vision, and data mining. This specialisation provides students with a solid theoretical understanding and practical skills on processing and analyzing digital data and the ability to create intelligent solutions to real world problems with modern AI techniques.
Computer Engineering focuses on both hardware and software aspects of computing with emphasis on embedded system development. In this specialisation, students also study signal processing and its applications, and work with projects on modern signal processors and embedded computers. The specialisation gives the students a good basis to work with Internet of Things (IoT) applications.
In addition to the core specialization options, students can take optional courses to widen their specialization expertise into:
• Biomedical signal analysis
• Machine learning
• Machine vision
• Signal processing
• Embedded systems
• Ubiquitous computing
This Master’s programme is provided by the Faculty of Information Technology and Electrical Engineering, and students are strongly encouraged to work closely with research groups in the faculty that are international leaders in their fields. The Center for Machine Vision and Signal Analysis (CMVS) is renowned world-wide for its 35 years of expertise in computer vision research. The Center for Ubiquitous Computing (UBICOMP) has created a unique research environment for Ubiquitous Computing including multitouch wall-sized displays, smartphone sensing middleware and sensor networks. Biomimetics and Intelligent Systems Group (BISG) is a fusion of expertise from the fields of computer science and biology. During the studies the research groups provide students trainee and master’s thesis positions, with the possibility to continue as a doctoral student, and even as a post-doctoral researcher.
The programme will provide the graduates with sufficient skills to work in a wide variety of positions offered by research institutes and companies mainly operating in the field of information and communications technology (ICT). The graduates are most likely to be employed in research and development related positions, but also management positions and entrepreneurship fit into the profile.
Possible titles include:
• Research Scientist
• Software Engineer
• System Designer
• Project Manager
Students applying for the programme must possess an applicable B.Sc. degree in computer science, electrical engineering or relevant fields such as physics or applied mathematics.
The Applied Mathematics group in the School of Mathematics at the University of Manchester has a long-standing international reputation for its research. Expertise in the group encompasses a broad range of topics, including Continuum Mechanics, Analysis & Dynamical Systems, Industrial & Applied Mathematics, Inverse Problems, Mathematical Finance, and Numerical Analysis & Scientific Computing. The group has a strongly interdisciplinary research ethos, which it pursues in areas such as Mathematics in the Life Sciences, Uncertainty Quantification & Data Science, and within the Manchester Centre for Nonlinear Dynamics.
The Applied Mathematics group offers the MSc in Applied Mathematics as an entry point to graduate study. The MSc has two pathways, reflecting the existing strengths within the group in numerical analysis and in industrial mathematics. The MSc consists of five core modules (total 75 credits) covering the main areas of mathematical techniques, modelling and computing skills necessary to become a modern applied mathematician. Students then choose three options, chosen from specific pathways in numerical analysis and industrial modelling (total 45 credits). Finally, a dissertation (60 credits) is undertaken with supervision from a member of staff in the applied mathematics group with the possibility of co-supervision with an industrial sponsor.
The course aims to develop core skills in applied mathematics and allows students to specialise in industrial modelling or numerical analysis, in preparation for study towards a PhD or a career using mathematics within industry. An important element is the course regarding transferable skills which will link with academics and employers to deliver important skills for a successful transition to a research career or the industrial workplace.
The course features a transferable skills module, with guest lectures from industrial partners. Some dissertation projects and short internships will also be available with industry.
Students take eight taught modules and write a dissertation. The taught modules feature a variety of teaching methods, including lectures, coursework, and computing and modelling projects (both individually and in groups). The modules on Scientific Computing and Transferable Skills particularly involve significant project work. Modules are examined through both coursework and examinations.
Assessment comprises course work, exams in January and May, followed by a dissertation carried out and written up between June and September. The dissertation counts for 60 credits of the 180 credits and is chosen from a range of available projects, including projects suggested by industrial partners.
Course unit details
CORE (75 credits)
* Introduction to Uncertainty Quantification
* Mathematical Methods
* Partial Differential Equations
* Scientific Computing
* Transferable Skills for Applied Mathematicians
OPTIONAL (3 modules, 45 credits)
* Applied Dynamical Systems (IM)
* Continuum Mechanics (IM)
* Stability theory (IM)
* Transport Phenomena and Conservation Laws (IM)
* Advanced Uncertainty Quantification (IM,NA)
* Approximation Theory and Finite Element Analysis (NA)
* Numerical Linear Algebra (NA)
* Numerical Optimization and Inverse Problems (NA)
Students registered on the Numerical Analysis pathway must select modules marked NA, and those registered on the Industrial Modelling pathway must select modules marked IM.
Syllabuses for the modules Introduction to Uncertainty Quantification and Advanced Uncertainty Quantification are currently being finalized and details will be added here as soon as possible.
Modern computing facilities are available to support the course.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
The programme will prepare students for a career in research (via entry into a PhD programme) or direct entry into industry. Possible subsequent PhD programmes would be those in mathematics, computer science, or one of the many science and engineering disciplines where applied mathematics is crucial. The programme develops many computational, analytical, and modelling skills, which are valued by a wide range of employers. Specialist skills in scientific computing are valued in the science, engineering, and financial sector.
Cloud computing is revolutionising the way that large, and often complex, datasets are stored and analysed. Our course aims to produce experts in cloud computing and big data required by academia and industry.
The MRes can only be applied for as part of the four-year (MRes plus PhD) EPSRC Centre for Doctoral Training in Cloud Computing for Big Data. The programme is suitable for students from both computing and mathematical backgrounds. It is very skills-focussed and also offers a high degree of research training.
Our course focuses on both theory and practice so that you can understand and implement cloud computing applications. You will cover key subjects such as advanced object-oriented programming, data mining and big data analytics.
All academic staff involved in teaching cloud computing modules have international reputations for their contributions to the field and some have extensive experience as practitioners in industry.
During the MRes you will undertake advanced Masters’ level training in cloud computing and data analytics. The training will begin with a module in either computing science for mathematicians (for those with a statistics background) or statistics for computing scientists (for those from a computer science background).
All students will then be taught topics including statistics for big data, programming for big data, cloud computing, machine learning, big data analytics and time series analysis. The taught component will finish with a substantial group project, where you will have the opportunity to work with students from different backgrounds on a practical industry-focused data analysis problem.
Following this in years 2-4, you will carry out PhD research, guided by PhD supervisors from within the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data, and typically additional advisors from industry.
You will have access to free cloud computing resources to manage your research, a purpose-built Decision Theatre and 3D visualisation facility and a 3D printing learning lab.
You will be based in The Core building, where you will have the opportunity to work alongside experts in key areas of computing science, as well as access to industrial partners. You will also receive funding to attend selected conferences in emerging areas of your research discipline. We also offer funding for equipment and software to support your research.