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If you are intrigued by the acquisition, processing, analysis and understanding of computer vision, this Masters is for you. The programme is offered by Surrey's Department of Electrical and Electronic Engineering, recognised for world-leading research in multimedia signal processing and machine learning. Read more
If you are intrigued by the acquisition, processing, analysis and understanding of computer vision, this Masters is for you.

The programme is offered by Surrey's Department of Electrical and Electronic Engineering, recognised for world-leading research in multimedia signal processing and machine learning.

PROGRAMME OVERVIEW

This degree provides in-depth training for students interested in a career in industry or in research-oriented institutions focused on image and video analysis, and deep learning.

State-of-the-art computer-vision and machine-learning approaches for image and video analysis are covered in the course, as well as low-level image processing methods.

Students also have the chance to substantially expand their programming skills through projects they undertake.

PROGRAMME STRUCTURE

This programme is studied full-time over 12 months and part-time over 48 months. It consists of eight taught modules and a standard project.

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.
-Digital Signal Processing A
-Object Oriented Design and C++
-Image Processing and Vision
-Space Robotics and Autonomy
-Satellite Remote Sensing
-Computer Vision and Pattern Recognition
-AI and AI Programming
-Advanced Signal Processing
-Image and Video Compression
-Standard Project

EDUCATIONAL AIMS OF THE PROGRAMME

The taught postgraduate degree programmes of the Department of Electronic Engineering are intended both to assist with professional career development within the relevant industry and, for a small number of students, to serve as a precursor to academic research.

Our philosophy is to integrate the acquisition of core engineering and scientific knowledge with the development of key practical skills (where relevant). To fulfil these objectives, the programme aims to:
-Attract well-qualified entrants, with a background in Electronic Engineering, Physical Sciences, Mathematics, Computing and Communications, from the UK, Europe and overseas.
-Provide participants with advanced knowledge, practical skills and understanding applicable to the MSc degree
-Develop participants' understanding of the underlying science, engineering, and technology, and enhance their ability to relate this to industrial practice
-Develop participants' critical and analytical powers so that they can effectively plan and execute individual research/design/development projects
-Provide a high level of flexibility in programme pattern and exit point
-Provide students with an extensive choice of taught modules, in subjects for which the Department has an international and UK research reputation

Intended capabilities for MSc graduates
-Know, understand and be able to apply the fundamental mathematical, scientific and engineering facts and principles that underpin computer vision, machine learning as well as how they can be related to robotics
-Be able to analyse problems within the field computer vision and more broadly in electronic engineering and find solutions
-Be able to use relevant workshop and laboratory tools and equipment, and have experience of using relevant task-specific software packages to perform engineering tasks
-Know, understand and be able to use the basic mathematical, scientific and engineering facts and principles associated with the topics within computer vision, machine learning
-Be aware of the societal and environmental context of his/her engineering activities
-Be aware of commercial, industrial and employment-related practices and issues likely to affect his/her engineering activities
-Be able to carry out research-and-development investigations
-Be able to design electronic circuits and electronic/software products and systems

Technical characteristics of the pathway
This programme in Computer Vision, Robotics and Machine Learning aims to provide a high-quality advanced training in aspects of computer vision for extracting information from image and video content or enhancing its visual quality using machine learning codes.

Computer vision technology uses sophisticated signal processing and data analysis methods to support access to visual information, whether it is for business, security, personal use or entertainment. The core modules cover the fundamentals of how to represent image and video information digitally, including processing, filtering and feature extraction techniques.

An important aspect of the programme is the software implementation of such processes. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspirations.

Key to the programme is cross-linking between core methods and systems for image and video analysis applications. The programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.

PROGRAMME LEARNING OUTCOMES

The Department's taught postgraduate programmes are designed to enhance the student's technical knowledge in the topics within the field that he/she has chosen to study, and to contribute to the Specific Learning Outcomes set down by the Institution of Engineering and Technology (IET) (which is the Professional Engineering body for electronic and electrical engineering) and to the General Learning Outcomes applicable to all university graduates.

General transferable skills
-Be able to use computers and basic IT tools effectively
-Be able to retrieve information from written and electronic sources
-Be able to apply critical but constructive thinking to received information
-Be able to study and learn effectively
-Be able to communicate effectively in writing and by oral presentations
-Be able to present quantitative data effectively, using appropriate methods

Time and resource management
-Be able to manage own time and resources
-Be able to develop, monitor and update a plan, in the light of changing circumstances
-Be able to reflect on own learning and performance, and plan its development/improvement, as a foundation for life-long learning

Underpinning learning
-Know and understand scientific principles necessary to underpin their education in electronic and electrical engineering, to enable appreciation of its scientific and engineering content, and to support their understanding of historical, current and future developments
-Know and understand the mathematical principles necessary to underpin their education in electronic and electrical engineering and to enable them to apply mathematical methods, tools and notations proficiently in the analysis and solution of engineering problems
-Be able to apply and integrate knowledge and understanding of other engineering disciplines to support study of electronic and electrical engineering

Engineering problem-solving
-Understand electronic and electrical engineering principles and be able to apply them to analyse key engineering processes
-Be able to identify, classify and describe the performance of systems and components through the use of analytical methods and modelling techniques
-Be able to apply mathematical and computer-based models to solve problems in electronic and electrical engineering, and be able to assess the limitations of particular cases
-Be able to apply quantitative methods relevant to electronic and electrical engineering, in order to solve engineering problems
-Understand and be able to apply a systems approach to electronic and electrical engineering problems

Engineering tools
-Have relevant workshop and laboratory skills
-Be able to write simple computer programs, be aware of the nature of microprocessor programming, and be aware of the nature of software design
-Be able to apply computer software packages relevant to electronic and electrical engineering, in order to solve engineering problems

Technical expertise
-Know and understand the facts, concepts, conventions, principles, mathematics and applications of the range of electronic and electrical engineering topics he/she has chosen to study
-Know the characteristics of particular materials, equipment, processes or products
-Have thorough understanding of current practice and limitations, and some appreciation of likely future developments
-Be aware of developing technologies related to electronic and electrical engineering
-Have comprehensive understanding of the scientific principles of electronic engineering and related disciplines
-Have comprehensive knowledge and understanding of mathematical and computer models relevant to electronic and electrical engineering, and an appreciation of their limitations
-Know and understand, at Master's level, the facts, concepts, conventions, principles, mathematics and applications of a range of engineering topics that he/she has chosen to study
-Have extensive knowledge of a wide range of engineering materials and components
-Understand concepts from a range of areas including some from outside engineering, and be able to apply them effectively in engineering projects

Societal and environmental context
-Understand the requirement for engineering activities to promote sustainable development
-Relevant part of: Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk issues
-Understand the need for a high level of professional and ethical conduct in engineering

Employment context
-Know and understand the commercial and economic context of electronic and electrical engineering processes
-Understand the contexts in which engineering knowledge can be applied (e.g. operations and management, technology development, etc.)
-Be aware of the nature of intellectual property
-Understand appropriate codes of practice and industry standards
-Be aware of quality issues
-Be able to apply engineering techniques taking account of a range of commercial and industrial constraints
-Understand the basics of financial accounting procedures relevant to engineering project work
-Be able to make general evaluations of commercial risks through some understanding of the basis of such risks
-Be aware of the framework of relevant legal requirements governing engineering activities, including personnel, health, safety and risk (including environmental risk) issues

Research and development
-Understand the use of technical literature and other information sources
-Be aware of the need, in appropriate cases, for experimentation during scientific investigations and during engineering development
-Be able to use fundamental knowledge to investigate new and emerging technologies
-Be able to extract data pertinent to an unfamiliar problem, and employ this data in solving the problem, using computer-based engineering tools when appropriate
-Be able to work with technical uncertainty

Design
-Understand the nature of the engineering design process
-Investigate and define a problem and identify constraints, including environmental and sustainability limitations, and health and safety and risk assessment issues
-Understand customer and user needs and the importance of considerations such as aesthetics
-Identify and manage cost drivers
-Use creativity to establish innovative solutions
-Ensure fitness for purpose and all aspects of the problem including production, operation, maintenance and disposal
-Manage the design process and evaluate outcomes
-Have wide knowledge and comprehensive understanding of design processes and methodologies and be able to apply and adapt them in unfamiliar situations
-Be able to generate an innovative design for products, systems, components or processes, to fulfil new needs

Project management
-Be able to work as a member of a team
-Be able to exercise leadership in a team
-Be able to work in a multidisciplinary environment
-Know about management techniques that may be used to achieve engineering objectives within the commercial and economic context of engineering processes
-Have extensive knowledge and understanding of management and business practices, and their limitations, and how these may be applied appropriately

FACILITIES, EQUIPMENT AND SUPPORT

To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.

We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.

Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by the Centre for Vision, Speech and Signal Processing (CVSSP).

CAREER PROSPECTS

Computer vision specialists are be valuable in all industries that require intelligent processing and interpretation of image and video. This includes industries in directly related fields such as:
-Multimedia indexing and retrieval (Google, Microsoft, Apple)
-Motion capture (Foundry)
-Media production (BBC, Foundry)
-Medical Imaging (Siemens)
-Security and Defence (BAE, EADS, Qinetiq)
-Robotics (SSTL)

Studying for Msc degree in Computer Vision offers variety, challenge and stimulation. It is not just the introduction to a rewarding career, but also offers an intellectually demanding and exciting opportunity to break through boundaries in research.

Many of the most remarkable advancements in the past 60 years have only been possible through the curiosity and ingenuity of engineers. Our graduates have a consistently strong record of gaining employment with leading companies.

Employers value the skills and experience that enable our graduates to make a positive contribution in their jobs from day one.

Our graduates are employed by companies across the electronics, information technology and communications industries. Recent employers include:
-BAE Systems
-BT
-Philips
-Hewlett Packard
-Logica
-Lucent Technologies
-BBC
-Motorola
-NEC Technologies
-Nokia
-Nortel Networks
-Red Hat

INDUSTRIAL COLLABORATIONS

We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
-Research and technology transfer projects with industrial partners such as the BBC, Foundry, LionHead and BAE
-A number of our academics offer MSc projects in collaboration with our industrial partners

RESEARCH PERSPECTIVES

This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.

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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Developed by the Bristol Robotics Laboratory, this Masters gives students unique exposure to world-leading robotics research, real-life automation and computer vision projects, and the opportunity for placements in UK companies to work on topical industry problems. Read more
Developed by the Bristol Robotics Laboratory, this Masters gives students unique exposure to world-leading robotics research, real-life automation and computer vision projects, and the opportunity for placements in UK companies to work on topical industry problems.

The last 20 years have seen a phenomenal growth in the development and application of computer and machine vision technology. With increasingly complex applications across diverse areas, including manufacturing, security and medicine, there is a growing need for professionals who can evaluate, design and implement technically appropriate and economically viable automation systems for enhancing quality and productivity.

The MSc in Automation and Computer Vision at UWE Bristol is one of the very few postgraduate courses that brings together both of these disciplines into one industry-focused, research-informed Masters.

Key benefits

Some students may be able to do an industry placement as part of their dissertation. Projects will be focused on real problems companies are working on. Those that don't go down the industry route will work at UWE Bristol on a topical research problem.

Course detail

The course provides a unique combination of these two overlapping disciplines, with a strong emphasis on robotics hardware for solving 'real-world' problems. You will develop both the technical knowledge and the business skills needed to introduce advanced automation and machine vision techniques in the workplace.

You will also benefit from the University's close links with industry, with guest lectures on many modules and the chance to work on real-life automation and computer vision projects.

Modules

• Automation and Control (30 credits)
• Machine Vision (30 credits)
• Managing finance (15 credits)
• Project management (15 credits)
• Industrial applications (15 credits)
• Industrial case studies (15 credits)

You will also work on an individual project (60 credits), which forms a major part of the course and gives you the chance to work on real-world research or industry projects

Format

Alongside the strong industry-focus of the course, you will have the opportunity to be part of, and work on, projects in the world-leading Bristol Robotics Laboratory, which brings together influential researchers in service robotics, autonomous systems and bio-engineering.

For those already working, we offer this course as a work-based learning course, as well as a standard full or part-time Masters. Employees of relevant industries can attend part of the course to supplement their existing skills or to be assessed on their current skills and knowledge of these highly topical subject areas.

Assessment

We will make use of a range of types of assessment on the course, including written exams, oral assessments and presentations, reports and project work and written assignments.

Careers / Further study

The course is a good grounding for wider careers in engineering, science, information technology, management and medical imaging. For those wishing to pursue further study, the course is also good preparation for a career in academia or research in fields such as computer vision, robotics, medical imaging, or more general engineering, science and information technology.

How to apply

Information on applications can be found at the following link: http://www1.uwe.ac.uk/study/applyingtouwebristol/postgraduateapplications.aspx

Funding

- New Postgraduate Master's loans for 2016/17 academic year –

The government are introducing a master’s loan scheme, whereby master’s students under 60 can access a loan of up to £10,000 as a contribution towards the cost of their study. This is part of the government’s long-term commitment to enhance support for postgraduate study.

Scholarships and other sources of funding are also available.

More information can be found here: http://www1.uwe.ac.uk/students/feesandfunding/fundingandscholarships/postgraduatefunding.aspx

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Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment. The studies combine both theoretical and practical approach. Read more
• 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
• Specialist

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.

For all enquiries, please refer to our enquiry form: http://www.oulu.fi/university/admissions-contact

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This MSc teaches advanced analytical and computational skills for success in a data rich world. Read more
This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

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The fields of graphics, vision and imaging increasingly rely on one another. Read more
The fields of graphics, vision and imaging increasingly rely on one another. This unique and timely MSc provides training in computer graphics, geometry processing, virtual reality, machine vision and imaging technology from world-leading experts, enabling students to specialise in any of these areas and gain a grounding in the others.

Degree information

Graduates will understand the basic mathematical principles underlying the development and application of new techniques in computer graphics and computer vision and will be aware of the range of algorithms and approaches available, and be able to design, develop and evaluate algorithms and methods for new problems, emerging technologies and applications.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits).

Core modules
-Mathematical Methods, Algorithmics and Implementation
-Image Processing
-Computer Graphics
-Research Methods

Optional modules
-Machine Vision
-Graphical Models
-Virtual Environments
-Geometry of Images
-Advanced Modelling, Rendering and Animation
-Inverse Problems in Imaging
-Computation Modelling for Biomedical Imaging
-Computational Photography and Capture
-Acquisition and Processing of 3D Geometry

Dissertation/report
All students undertake an independent research project related to a problem of industrial interest or on a topic near the leading edge of research, which culminates in a 60–80 page dissertation.

Teaching and learning
The programme is delivered through a combination of lectures and tutorials. Lectures are often supported by laboratory work with help from demonstrators. Student performance is assessed by unseen written examinations, coursework and a substantial individual project.

Careers

Graduates are ready for employment in a wide range of high-technology companies and will be able to contribute to maintaining and enhancing the UK's position in these important and expanding areas. The MSc provides graduates with the up-to-date technical skills required to support a wealth of research and development opportunities in broad areas of computer science and engineering, such as multimedia applications, medicine, architecture, film animation and computer games. Our market research shows that the leading companies in these areas demand the deep technical knowledge that this programme provides. Graduates have found positions at global companies such as Disney, Sony and Siemens. Others have gone on to PhD programmes at MIT, Princeton University, and Eth Zurich.

Top career destinations for this degree:
-Senior Post-Doctoral Research Associate, University of Oxford
-Software Engineer, Sengtian Software
-Graduate Software Engineer, ARM
-IT Officer, Nalys
-MSc in Computer Games and Entertainment, Goldsmiths, University of London

Employability
UCL Computer Science was one of the top-rated departments in the country, according to the UK Government's most recent research assessment exercise, and our graduates have some of the highest employment rates of any university in the UK. This degree programme also provides a foundation for further PhD study or industrial research.

Why study this degree at UCL?

UCL Computer Science contains some of the world's leading researchers in computer graphics, geometry processing, computer vision and virtual environments.

Research activities include geometric acquisition and 3D fabrication, real-time photo-realistic rendering, mixed and augmented reality, face recognition, content-based image-database search, video-texture modelling, depth perception in stereo vision, colour imaging for industrial inspection, mapping brain function and connectivity and tracking for SLAM (simultaneous localisation and mapping).

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Automation, control and robotics are pervasive enabling technologies found in almost every modern technical system, particularly in manufacturing and production. Read more
Automation, control and robotics are pervasive enabling technologies found in almost every modern technical system, particularly in manufacturing and production. They combine the diverse and rapidly expanding disciplines of automation, control, mechanics, software and signal processing.

This course is ideal if you wish to develop comprehensive knowledge and understanding of
-Classical and modern control theory.
-Industrial automation.
-Systems analysis.
-Design and simulation.
-Robotics.

You gain the ability to apply principles of modelling, classical and modern control concepts and controller design packages in various areas of industry. You also learn how to design and exploit automation and robotic systems in a range of manufacturing and industrial applications.

The course has six core modules which cover the major aspects of industrial automation and control systems engineering and robotics, ranging from classical linear control system design to non-linear, optimal and intelligent control systems, including distributed control systems, robotics, computer networks and artificial intelligence.

You also choose two optional modules relevant to automation and control to suit your interests. For example, if you wish to work in the manufacturing industry you can choose manufacturing systems or machine vision. There is the opportunity to study one or two management modules if you wish to apply yourself to a more managerial role.

To gain the masters you complete a major research-based project, which can be focused on an area of your particular interest or career need.

You work alongside staff from the Electrical, Electronic and Control Engineering Group and the Centre for Automation and Robotics Research (CARR) at Sheffield Hallam. This provides the opportunity to work with active researchers.

For more information, see the website: https://www.shu.ac.uk/study-here/find-a-course/msc-automation-control-and-robotics

Professional recognition

This course is seeking accreditation by the Institution of Engineering and Technology (IET) on behalf of the Engineering Council for the purposes of fully meeting the academic requirements for registration as a Chartered Engineer. The MSc will meet, in part, the exemplifying academic benchmark requirements for registration as a Chartered Engineer; graduates who have a BEng (Hons) accredited for CEng will be able to show that they have satisfied the further learning requirement for CEng accreditation.

Course structure

Full time – 12 to 18 months.
Part time – 3 years.
Start dates September and January.

Core modules
-Industrial automation
-Control of linear systems
-Advanced control methods
-Robotics
-Computer networks
-Applicable artificial intelligence

Options
Choose two from:
-Software engineering
-Project and quality management
-Sustainability, energy and environmental management
-Machine vision
-Digital signals processing
-Manufacturing systems

MSc
-Project and dissertation

Assessment: coursework, examination, presentation, MSc project report.

Other admission requirements

International students
India: a first class BE in a relevant discipline, or a good second class BE with a strong performance in mechanical and manufacturing subjects.

China: a four year Bachelors degree in a relevant discipline, with an overall average of at least 80 per cent or equivalent.

Other countries: a good honours degree or equivalent in a relevant subject.

Overseas applicants from countries whose first language is not English must normally produce evidence of competence in English. An IELTS score of 6.0 with 5.5 in all skills (or equivalent) is the standard for non-native speakers of English. If your English language skill is currently below an IELTS score of 6.0 with a minimum of 5.5 in all skills we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English level.

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What if your smartphone could recognise that it was you before switching on, and could sense your mood by recognising your facial expressions? What if you… Read more
What if your smartphone could recognise that it was you before switching on, and could sense your mood by recognising your facial expressions? What if you could use a real thumbs-up for 'liking' things on Facebook? How can you play games on an Xbox using only your body gestures? How can you equip cars with in-vehicle technology that could automatically read road signs? These are just some of the fascinating questions that you will strive to answer on this programme.

This programme is intended to respond to a growing skills shortage in research and industry for engineers with a high level of training in the analysis and interpretation of images and video. It covers both low-level image processing and high-level interpretation using state-of-the-art machine learning methodologies. In addition, it offers high-level training in programming languages, tools and methods that are necessary for the design and implementation of practical computer vision systems.

Modules Can Include:
Advanced Transform Methods
Machine Learning
Introduction to Computer Vision
Computer Graphics
Artificial Intelligence
Techniques for Computer Vision
High Performance Computing
C++ for Image Processing
Project

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Machine learning, data mining and high-performance computing are concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Read more
Machine learning, data mining and high-performance computing are concerned with the automated analysis of large-scale data by computer, in order to extract the useful knowledge hidden in it. Using state-of-the-art artificial intelligence methods, this technology builds computer systems capable of learning from past experience, allowing them to adapt to new tasks, predict future developments, and provide intelligent decision support. Bristol's recent investment in the BlueCrystal supercomputer - and our Exabyte University research theme - show our commitment to research at the cutting edge in this area.

This programme is aimed at giving you a solid grounding in machine learning, data mining and high-performance computing technology, and will equip you with the skills necessary to construct and apply these tools and techniques to the solution of complex scientific and business problems.

Programme structure

Your course will cover the following core subjects:
-Introduction to Machine Learning
-Research Skills
-Statistical Pattern Recognition
-Uncertainty Modelling for Intelligent Systems

Depending on previous experience or preference, you are then able to take optional units which typically include:
-Artificial Intelligence with Logic Programming
-Bio-inspired Artificial Intelligence
-Cloud Computing
-Computational Bioinformatics
-Computational Genomics and Bioinformatics Algorithms
-Computational Neuroscience
-High Performance Computing
-Image Processing and Computer Vision
-Robotics Systems
-Server Software
-Web Technologies

You must then complete a project that involves researching, planning and implementing a major piece of work. The project must contain a significant scientific or technical component and will usually involve a software development component. It is usually submitted in September.

This programme is updated on an ongoing basis to keep it at the forefront of the discipline. Please refer to the University's programme catalogue for the latest information on the most up-to-date programme structure.

Careers

Skilled professionals and researchers who are able to apply these technologies to current problems are in high demand in today's job market.

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This advanced course focuses on enabling you to become proficient in communicating across a range of different disciplines and delivering optimised engineering solutions using an integrated multidisciplinary mechatronics approach. Read more

About the course

This advanced course focuses on enabling you to become proficient in communicating across a range of different disciplines and delivering optimised engineering solutions using an integrated multidisciplinary mechatronics approach. You will be exposed to a broad range of engineering disciplines, be able to solve multidisciplinary mechatronics problems and develop the skills to apply a mechatronic approach to the solution of technical problems.

Reasons to Study

• Accredited by the Institution of Engineering and Technology (IET)
ensuring you will benefit from the highest quality teaching, and graduate with a recognised qualification

• Graduate employability
Mechatronic engineers are in high demand as more industries seek to apply advances across a range of engineering disciplines

• Enjoy access to state-of-the-art facilities
including dedicated mechanical, electrical and electronic laboratories especially suited for mechatronics, as well as an for the manufacture of student designs

• Industry placement opportunity
you can chose to undertake a year-long work placement, gaining valuable experience to enhance your practical and professional skills further

• Work with leading research groups
you will be offered opportunities to work on projects with research groups within the faculty, including the Centre for Advanced Manufacturing Processes and Mechatronics, that are engaged in high-class, research and industrial collaboration and consultancy

• Course content relevant to modern day practice
our research informs our teaching, ensuring the course content covers current industry topics and issues

• Excellent graduate prospects
graduates enjoy exciting career opportunities in a range of fields such as robotics and automation, manufacturing, aerospace, material processing, energy and power.

Modules

First semester (September to January)

• Electromechanics
• Mechatronic Systems - Engineering and Design
• Engineering Business Environment and Energy Studies
• Programming and Software Engineering

Second semester (February to May)

• Machine Vision, Robotics and Flexible Automation
• Engineering Systems: Dynamics and Control
• Microprocessor Applications and Digital Signal Processing
• Research Methods

Individual Project (Stage three)

This research can be industrially-based or linked to an industrial partner, attached to one of the mechatronic-related research teams within the faculty or in other collaborating institutions. The research project should be in an area relevant to Mechatronics, where clear evidence of the ability to solve a real multidisciplinary problem is demonstrated. The project assessment involves a formal presentation, production of a technical paper and a thesis.

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

Teaching is delivered through a variety of methods including lectures, tutorials and laboratories. You will be expected to undertake self-directed study.

Contact and learning hours

For taught sessions you will attend eight modules with a total of 48 hours (four hours per week for 12 weeks each), with eight hours per module per week of average additional self-directed study. For the individual project you normally will spend 13 weeks working five days (eight hours per day) a week to complete it, and have one hour per week contact time with your supervisor.

Academic expertise

Research is carried out by the Mechatronics Research Centre, which holds a considerable number of UK and EU research project grants and has collaborative research links with more than 100 national and international organisations. The group is internationally regarded and specialises in machine design, control and simulation, fluid power systems and motion control.

As part of your studies, you will be offered opportunities to work on projects with research groups within the faculty that are engaged in high-class, leading-edge research and industrial collaboration and consultancy.

During the project element of the course, the Intelligent Machines and Automation Systems (IMAS) Research Laboratory provides access to dedicated research facilities

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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Engineering is constantly changing, and graduates often need to deepen their technical skills and understanding. This course is especially relevant for mechanical and manufacturing engineers and technicians wishing to broaden their industrial and managerial skills. Read more
Engineering is constantly changing, and graduates often need to deepen their technical skills and understanding.

This course is especially relevant for mechanical and manufacturing engineers and technicians wishing to broaden their industrial and managerial skills. It is ideal for continuing professional development and updating technical skills.

You study eight taught modules drawn from a wide choice of technical and management modules. This gives you advanced tuition in areas of engineering tailored to your career needs such as design, manufacturing, materials, networking or electronics and telecommunications.

We emphasise applying knowledge to relevant workplace skills in areas such as:
-Design, manufacture, electronics, telecommunications and information technology, networking and materials.
-Core management disciplines of quality, finance and marketing and others.

The international product development module involves working in multidisciplinary teams to design and develop a product in the global market.

This flexible course helps you to develop your career based your needs, and helps you on your path towards Chartered Engineer status.

For more information, see the website: https://www.shu.ac.uk/study-here/find-a-course/msc-advanced-engineering

Professional recognition

Accredited by the Institute of Materials, Minerals and Mining (IOM3).

Accredited by the Institution of Mechanical Engineers (IMechE) on behalf of the Engineering Council for the purposes of fully meeting the academic requirement for registration as a Chartered Engineer. Accredited MSc graduates who also have a BEng (Hons) accredited for CEng, will be able to show that they have satisfied the educational base for CEng registration. It should be noted that graduates from an accredited MSc programme, who do not also have an appropriately accredited Honours degree, will not be regarded as having the exemplifying qualifications for professional registration as a Chartered Engineer with the Engineering Council; and will need to have their first qualification individually assessed through the Individual Case Procedure if they wish to progress to CEng.

This programme is CEng accredited by the Institution of Engineering and Technology (IET) and fulfils the educational requirements for registration as a Chartered Engineer when presented with an CEng accredited Bachelors programme.

Course structure

Full time – 12 to 18 months.
Part time – typically 3 years, maximum 6 years.
Starts September and January.

Course design
You choose a combination of management, technical and optional modules from a choice of 36. Your choice must total eight 15-credit modules and be agreed with your course leader. At least four must be technical modules.

Optional management modules
-Finance and marketing
-Project and quality management
-Management of strategy, change and innovation
-Lean operations and six sigma
-Manufacturing systems

Optional technical modules
-Group project - international product development
-Competitive materials technology
-Advanced CAD/CAM
-Competitive design for manufacture
-Advanced manufacturing technology
-Advanced metallic materials
-Sustainability, energy and environmental management
-Computer networks
-Communication media
-Network applications
-Communication engineering
-Digital signal processing
-Applicable artificial intelligence
-Microprocessor engineering
-Software engineering
-Operating systems
-Object oriented methods
-Digital electronic system design
-VLSI design
-Industrial applications of finite element methods
-Industrial automation
-Robotics
-Machine vision
-Equipment engineering and design
-Control of linear systems
-Advanced investigatory techniques for materials engineers
-Advanced control methods
-Advanced vibration and acoustics

MSc
-Project and dissertation (60 credits)

Assessment: by final examination; coursework and project reports.

Other admission requirements

Overseas applicants from countries whose first language is not English must normally produce evidence of competence in English. An IELTS score of 6.0 with 5.5 in all skills (or equivalent) is the standard for non-native speakers of English. If your English language skill is currently below an IELTS score of 6.0 with a minimum of 5.5 in all skills we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English level.

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This course is for engineers or graduates who want to become technical specialists or managers in industrial and manufacturing companies. Read more
This course is for engineers or graduates who want to become technical specialists or managers in industrial and manufacturing companies.

It increases your career potential by improving your:
-Knowledge and experience of engineering.
-Technical and problem solving skills.
-Management skills.
-Ability to take on greater responsibility.

This course helps you understand concepts and theories behind developing, manufacturing and managing engineering products and systems. You learn to explore and apply developments in engineering and management academic thinking and industrial practice.

You study:
-Two management modules.
-Two technical modules.
-Four optional modules.

There is a wide range of optional modules including:
-Lean operations and six sigma.
-Advanced manufacturing technology.
-Applicable artificial intelligence.
-Computer-aided design/computer-aided manufacture.
-Advanced computer system architecture.
-Network applications.

The international product development module involves working in multidisciplinary teams to develop a new product in a global market. This allows you to develop much sought after advanced technical and business skills and improves your career prospects in engineering industry, and public service. This project also develops your particular interest in a supported environment.

For more information, see the website: https://www.shu.ac.uk/study-here/find-a-course/msc-advanced-engineering-and-management

Professional recognition

This course is accredited by the Institute of Materials, Minerals and Mining (IOM3).

This course is accredited by the Institution of Mechanical Engineers (IMechE) on behalf of the Engineering Council for the purposes of fully meeting the academic requirement for registration as a Chartered Engineer. Accredited MSc graduates who also have a BEng (Hons) accredited for CEng, will be able to show that they have satisfied the educational base for CEng registration. It should be noted that graduates from an accredited MSc programme, who do not also have an appropriately accredited Honours degree, will not be regarded as having the exemplifying qualifications for professional registration as a Chartered Engineer with the Engineering Council; and will need to have their first qualification individually assessed through the Individual Case Procedure if they wish to progress to CEng.

This programme is CEng accredited by the Institution of Engineering and Technology (IET) and fulfils the educational requirements for registration as a Chartered Engineer when presented with an CEng accredited Bachelors programme.

Course structure

Full time – 12 to 18 months.
Part time – typically 3 years, maximum 6 years.
Starts September and January.

Core management modules
-Finance and marketing
-Project and quality management

Core technical modules
-Group project – international product development
-Sustainability, energy and environmental management

Optional modules (two from)
-Lean operations and six sigma
-Management of strategy, change and innovation
-Manufacturing systems

Plus two from:
-Advanced control methods
-Advanced investigatory techniques for materials engineers
-Advanced manufacturing technology
-Advanced metallic materials
-Advanced vibration and acoustics
-Applicable artificial intelligence
-Computer-aided design/computer-aided manufacturing
-Communication engineering
-Communication media
-Computer networks
-Competitive design for manufacture
-Competitive materials technology
-Control of linear systems
-Digital electronics system design
-Digital signal processing
-Embedded systems
-Equipment engineering and design
-Industrial applications of finite element methods
-Industrial automation
-Machine vision
-Microprocessor engineering
-Advanced computer system architecture
-Network applications
-Object-oriented methods
-Operating systems
-Robotics
-Software engineering
-VSLI

MSc
-Project and dissertation

Assessment: examination; coursework; project reports.

Other admission requirements

International students
If English is not your first language you typically need an IELTS 6.0 score with a minimum of 6.0 in writing and 5.5 in all other skills or equivalent. If your English language skill is currently below IELTS 6.0 we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English score.

India
-A first class BE in an relevant discipline, or a good second class BE with a strong performance in mechanical and manufacturing subjects.
China
-A four year Bachelors degree in an relevant discipline, with an overall average of at least 80 per cent or equivalent.
Other countries
-A good honours degree or equivalent in an relevant subject.

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This programme will not have a 2016 intake as the content is being extensively improved. The programme aims to offer a rational, flexibly structured. Read more

NOTE

This programme will not have a 2016 intake as the content is being extensively improved.

OVERVIEW

The programme aims to offer a rational, flexibly structured
and coherent postgraduate study in Automatic Control. While
providing advanced general knowledge in Electronic Engineering, the programme is specifically focussed on nonlinear control principles, measurement instrumentation, simulations and implementation of feedback control.
The programme is designed to provide specific skills for individuals who wish to become a control engineer in manufacturing or research and development in industry sectors, or to pursue a PhD in control engineering.

With a track record of 20 years, the research group Control & Intelligent Control Systems Engineering at the University of Hull has an international reputation for its initiatives in the field of fault diagnostics of dynamic systems. This expertise along with its staff’s teaching experience in control engineering supports the masters programme.

OBJECTIVES

The course will provide students with:
• advanced knowledge of control principles including
multivariable feedback control and nonlinear control
systems,
• essential knowledge of control systems configuration,
algorithm design and evaluation,
• a general knowledge of advanced computer simulation
and measurement instrumentation,
• skills in the software and hardware implementation of
control the latest computer modelling and simulation
techniques,
• research experience in control applications in the
engineering field,
• experience of undertaking a significant relevant
research project

SUBJECTS COVERED

• Multivariable feedback control
• Robotic manipulator control
• Machine vision
• Applied Optoelectronics
• Time Signal Processing and Integrated Circuit Design
• Low Power/Voltage Design and VHDL
• Advanced Digital Systems Design
• Microwave Devices, Techniques and Measurements
• Communication Systems
• Intellectual property rights
• Research skills and project planning

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This programme will not have a 2016 intake as the content is being extensively improved. Microcontrollers are being designed into more and more products e.g. Read more

NOTE

This programme will not have a 2016 intake as the content is being extensively improved.

Overview

Microcontrollers are being designed into more and more products e.g. motor cars, washing machines, mobile phones etc. The fast growing and challenging area of embedded systems requires engineers with hardware and software design capabilities for use in this variety of situations. This advanced programme of study offers a natural progression route for graduates in electrical and electronic engineering, physics, computer science, or related disciplines, and is structured to provide the student with the necessary skills for embedded systems development.

Aims and Objectives

To provide knowledge of electronic systems design based around microcontrollers
To provide the ability to manage new technologies and integrate them into system design
To satisfy the growing demand for engineers with embedded systems experience
To facilitate professional development of the student that will lead to a successful professional career

Distinctive features

MSc in Embedded Systems is for students who wish to study a programme to engage them in system development and design focussing on microcontrollers, both hardware and software. It will provide advanced knowledge in areas essential for this type of design and development, whilst also providing learning in areas closely associated to embedded systems such as control and communications.

Modular structure

The course conforms to the standard University of Hull structure, consisting of two taught semesters (the Diploma stage) followed by a substantial individual project. Core modules are compulsory; choice of optional modules is based on student preferences.

Core:

Advanced Digital Systems Design (Semester 1)
Product Planning and Design Exercise (Semester 1)
Complex Circuits and Systems (Semester 2)
Advanced Discreet Time Signal Processing and Integrated Circuit Design (Semesters 1 and 2)
Dissertation project

Options:

Mobile Radio
Propagation and Antennas
Advanced Control
Radio Frequency and Microwave Devices
Techniques and Measurements
Machine Vision

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There is a significant demand in Engineers trained beyond the Bachelor level. MSc in Electronic Engineering provides a rational, flexibly structured and coherent postgraduate study. Read more

Overview

There is a significant demand in Engineers trained beyond the Bachelor level. MSc in Electronic Engineering provides a rational, flexibly structured and coherent postgraduate study. The students will achieve a profound knowledge base in a wide area of Electronic Engineering. In additions, they will develop wider skills in IT, communication, problem solving, team working and time/task management. As a result, the programme will provide a springboard to a successful career to the mutual benefit of the individual, the economy and society.

Aims and Objectives

To satisfy demand in Engineers trained beyond the Bachelor level;
To provide sound general knowledge in advanced Electronic Engineering;
To present an intellectual challenge to the students
To facilitate professional development of the student that will lead to a successful professional career.

Distinctive features

MSc in Electronic Engineering is for students who wish to study a generic programme which is not biased towards a specialization. It will provide advanced knowledge in a broad range of Electronic Engineering without being focussed on a particular area. The programme is very flexible with a large range of choice options to accommodate candidates’ preferences. The candidates will gain both subject-specific and more generic skills. The programme combines academic depth with current industrial practice in the context of real engineering applications.

Modular structure

The course conforms to the standard University of Hull structure, consisting of two taught semesters (the Diploma stage) followed by a substantial individual project. Core modules are compulsory; choice of optional modules is based on student preferences.

Core:

Product Planning and Design Exercise (Semester 1)
Complex Circuits and Systems (Semester 2)
Dissertation project

Options:

Advanced Digital Systems Design
Advanced Discreet Time Signal Processing and Integrated Circuit Design
Applied Optoelectronics
Advanced Control
Control and Robotics
Machine Vision
Communication Systems
Mobile Radio
Propagation and Antennas
Radio Frequency and Microwave Devices
Techniques and Measurements

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The increased need for communications in modern day society has led to the development of a complex global communication infrastructure that uses the latest wireless and wired technologies for the communication of information. Read more
The increased need for communications in modern day society has led to the development of a complex global communication infrastructure that uses the latest wireless and wired technologies for the communication of information. To keep up with the increasing demands placed on this infrastructure requires engineers with the latest knowledge of and skills in current and emerging technologies.

Studying this course enables you to gain an advanced understanding of current telecommunications and electronic systems and acquire the skills necessary for their design, development and maintenance. You study key technical areas such as digital electronics and communications with the option of selecting management modules to develop your project and managerial ability.

A number of option modules ranging from artificial intelligence to software engineering allow you to focus your studies towards your career aspirations and tailor the course to your requirements. As well as improving your technical skills and knowledge, we also focus on building wider professional skills, such as planning, research techniques and promoting innovation.

We emphasise learning through practical investigations and problem solving, where you explore the complex issues that are typical of modern telecommunication systems typically through real world case studies. You complete a major project, supported by a project tutor, in an area of your choice allowing you to focus on a topic that can contribute to your career aims.

For more information, see the website: https://www.shu.ac.uk/study-here/find-a-course/msc-telecommunication-and-electronic-engineering

Professional recognition

This programme is CEng accredited by the Institution of Engineering and Technology (IET) and fulfils the educational requirements for registration as a Chartered Engineer when presented with an CEng accredited Bachelors programme.

Course structure

Full time – 12 to 18 months.
Part time – typically 3 years, maximum 6 years.
Starts September and January.

Core modules
-Communication media
-Digital electronic system design
-Project

Management modules (choose up to two from)
-Finance and marketing
-Management of strategy, change and innovation
-Project and quality management

Options (choose up to six from)
-Advanced control methods
-Applicable artificial intelligence
-Business process management
-Communication engineering
-Computer networks
-Control of linear systems
-Microprocessor engineering
-Digital signal processing
-Group project – international product development
-Network applications
-Object-oriented methods
-Operating systems
-Software engineering
-VLSI design
-Machine vision
-Embedded systems

Assessment: coursework, examinations, project reports.

Other admission requirements

Overseas applicants from countries whose first language is not English must normally produce evidence of competence in English. An IELTS score of 6.0 with 5.5 in all skills (or equivalent) is the standard for non-native speakers of English. If your English language skill is currently below an IELTS score of 6.0 with a minimum of 5.5 in all skills we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English level.

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