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Masters Degrees (Machine Vision)

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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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Application period/deadline. November 1, 2017 - January 24, 2018. Research-oriented degree provides an exciting opportunity to study in a leading-edge research environment. Read more

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

• 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.

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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. Read more

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.

Read about the experience of a previous student on this course, Gianmarco Addari.

Programme structure

This programme is studied full-time over 12 months and part-time from 24 to 60 months. It consists of eight taught modules and a standard project. 

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.

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.

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.

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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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.

About this degree

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 two core modules (30 credits), four to six optional modules (60 to 90 credits), up to two elective modules (up to 30 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 (15 credits)
  • Statistical Modelling and Data Analysis (15 credits)

Optional modules

Students must choose 15 credits from Group One Options. Of the remaining credits, students must choose a minimum of 30 and a maximum of 60 from Group Two, 15 credits from Group Three and a maximum of 30 credits from Electives.

Group One Options (15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Group Two Options (30 to 60 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Statistical Natural Language Processing (15 credits)

Group Three Options (15 credits)

  • Applied Bayesian Methods (15 credits)
  • Statistical Design of Investigations (15 credits)
  • Statistical Inference (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

A list of acceptable elective modules is available on the Departmental page.

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.

Further information on modules and degree structure is available on the department website: Computational Statistics and Machine Learning MSc

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.

Recent career destinations for this degree

  • Data Scientist, Interpretive
  • Software Engineer, Google
  • Data Scientist, YouGov
  • Research Engineer, DeepMind
  • PhD in Computer Science, UCL

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.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

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 the 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.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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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.

About this degree

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

  • Computer Graphics (15 credits)
  • Image Processing (15 credits)
  • Mathematical Methods, Algorithmics and Implementations (15 credits)
  • Research Methods and Reading (15 credits)

Optional modules

Students must choose a minimum of 15 and a maximum of 30 credits from Group One options. Students must choose a minimum of 30 and a maximum of 45 credits from Group Two options.

Group One Options (15 to 30 credits)

  • Machine Vision (15 credits)
  • Virtual Environments (15 credits)

Group Two Options (30 to 45 credits)

  • Acquisition and Processing of 3D Geometry (15 credits)
  • Computational Modelling for Biomedical Imaging (15 credits)
  • Computational Photography and Capture (15 credits)
  • Geometry of Images (15 credits)
  • Graphical Models (15 credits)
  • Information Processing in Medical Imaging (15 credits)
  • Introduction to Machine Learning (15 credits)
  • Inverse Problems in Imaging (15 credits)
  • Numerical Optimisation (15 credits)
  • Robotic Sensing, Manipulation and Interaction (15 credits)
  • Robotic Vision and Navigation (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

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.

Further information on modules and degree structure is available on the department website: Computer Graphics, Vision and Imaging MSc

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 leading universities worldwide.

Recent career destinations for this degree

  • Business Analyst, Adobe
  • Software Engineer, FactSet Research Systems
  • MRes in Engineering, Imperial College London
  • Software Engineer, Sengtian Software
  • PhD in Computer Graphics, UCL

Employability

UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

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.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

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).

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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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.

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

Core modules

  • industrial automation
  • control of linear systems
  • advanced control methods
  • robotics
  • applicable artificial intelligence

Options

Choose two from

  • software engineering
  • computer networks
  • project and quality management
  • sustainability, energy and environmental management
  • machine vision
  • digital signals processing
  • manufacturing systems
  • mixed signal design
  • electrical energy systems
  • efficient machines and electromagnetic applications.

MSc

  • project and dissertation

Assessment

  • coursework
  • examination
  • presentation
  • MSc project report

Employability

This course provides you with the knowledge and skills for further advanced study in this area.

You can also apply your skills in an industrial setting for automated manufacturing, control system design, or in the wide range of industries that exploit intelligent robotics. Graduates from this course find career opportunities in areas including • automation and control • process and petrochemical • biomedical • manufacturing • energy • automotive • aerospace.

You can also pursue careers in engineering design and development, engineering research, engineering consultancy and engineering management.

Completing this course combined with further work-based experience enables you to gain Chartered Engineer status.



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This programme aims to give students professional knowledge and skills for a successful career in the future that are orientated to engineering technologies… Read more

This programme aims to give students professional knowledge and skills for a successful career in the future that are orientated to engineering technologies, such as mechatronics, robotics and automation, which presume professional abilities to integrate, conduct and lead complex engineering projects integrating ICT and hardware technologies for solving practical problems and starting a new business. This programme is strongly orientated towards practical, hands-on projects and developing practical skills supported by laboratories of mechatronics, robotics, machine vision, metrology and measurement technology and computer classes.

Most of the courses are project based supported by theoretical materals. There is a project course on the first year containing the topics of machine vision and mechatronics systems aimed to support development of a real automation or robotic systems by student groups ending with presenting a conference paper as a rule. Examples of this kind projects are „Quadrocopter gesture control sytem“, „Automated inspection system of electric motor staator and rootor sheets“ and „Development of the camera system for the nanosatellite“, etc.

Future belongs to the specialities which provide flexible and integrated deep technical knowledge as it is the case in Mechatronics curricula. A good proof of this is the fact that Forbes nominates two MSc Mechatronics graduates among the EU most successful young leaders and entrepreneurs in Industry and Science in 2015.

Key features

  • The programme offers a unique opportunity to acquire integrated knowledge and skills in electrical/electronics and mechanical engineering along with deep ICT knowledge by the courses from the faculties of Mechanical Engineering, Information Technology and Power Engineering
  • Strong orientation towards facilitating the development of business and entrepreneurial skills, supported by strong practical course projects
  • The programme conforms to internationally recognized professional mechatronics engineering qualification standards
  • Double Degree option in MSc Mechatronics in collaboration with ITMO University St. Petersburg http://en.ifmo.ru/
  • Semester or internship abroad in world leading universities by support of Erasmus+ programme
  • Scholarships available for the best students

Curriculum

Structure of curriculum

Future career options

The graduates of the programme possess skills applicable in a broad sphere, such as automation and robotics engineers in industry; project managers and entrepreneurs and managers of innovative SMEs orientated towards developing cutting edge technology or medicinal devices; health and space industry; security; products combining hardware and ICT, etc. Active and bright mechatronics engineers are urgently needed in the fields of automatic production lines and robotics such as ABB or SIEMENS. Students can also continue their studies at PhD level in mechatronics or in a related field.



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Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry. Read more

Learn how to research, design and develop machine learning and autonomous systems technologies. You’ll be prepared for a wide range of careers in industry.

Intelligent and autonomous systems are increasingly important in all areas of human life and activity from medicine and space exploration to agriculture and entertainment.

Understanding and developing autonomous systems involves a range of skills and knowledge including designing interactive systems with both human and machine elements, and modelling and building systems that can sense and learn.

Machine learning is at the heart of autonomous and intelligent systems, including computer vision and robotics. It also underpins the recent developments in data analytics across many fields.

You will learn to use new knowledge to solve complex machine learning and autonomous systems problems. You’ll develop a range of skills including the theory of machine learning, artificial intelligence, autonomous systems design and engineering, and the implications for humans of interacting more and more with intelligent and autonomous systems.

You will be taught by academics from the Department of Computer Science with expertise in machine learning, autonomous systems, artificial intelligence and human-computer interaction. This course has been designed in collaboration with the Department of Electronic and Electrical Engineering who offer expertise in robotics.

You will study in a research-led department with a supportive postgraduate community. You’ll learn in our bespoke computer laboratory and be exposed to the latest ideas and technology. The department has strong links to industry both nationally and internationally.

With machine learning and autonomous systems forming an essential part of a number of key industries, our MSc graduates will be highly sought after by employers.

You’ll gain the knowledge and transferable skills for a career in a wide range of industries, or for further study at PhD level. Graduates from the department have gone on to work in a wide variety of sectors, including IT consultancy, software development, banking and education.

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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.

Professional recognition

This course is accredited by the Institute of Materials, Minerals and Mining (IOM3), on behalf of the Engineering Council, for the purposes of partly meeting the academic requirement 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.

This course is also accredited by the Institution of Mechanical Engineers (IMechE) on behalf of the Engineering Council and will meet, in part, the exemplifying academic benchmark requirements 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

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    

Employability

Graduates in technical subjects can broaden their experience in mechanical manufacturing, electronics and information technology, networking, materials and management areas.

The flexible choice of modules allows you to tailor the course to your particular needs and this can enhance career prospects in the engineering industry, research, teaching and public service.

   



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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.

Professional recognition

This course is accredited by the Institute of Materials, Minerals and Mining (IOM3), on behalf of the Engineering Council, for the purposes of partly meeting the academic requirement 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.

This course is also accredited by the Institution of Mechanical Engineers (IMechE) on behalf of the Engineering Council and will meet, in part, the exemplifying academic benchmark requirements 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

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

Employability

If you are a new graduate, this course gives you the knowledge and skills to begin a career as a technical specialist or manager. If you are already employed in engineering, it improves you career potential and can lead to roles with greater responsibility.

It can also help towards a career teaching engineering.



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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.

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

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 • 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 • machine vision • embedded systems • mixed signal design • electrical energy systems • efficient machines and electromagnetic applications.

Assessment

  • coursework
  • examinations
  • project reports

Employability

One of the primary motivations in developing this course is to enhance your employability or to allow you to progress to higher levels of study such as academic research.

You can consider employment in a number of areas of telecommunications and electronics at senior and management level or alternatively undertake further study by working towards a research degree and pursue a career possibly in academia.



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The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain. Read more

The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study the subject. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

About this degree

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Students undertake modules to the value of 180 credits.

The programme consists of one core module (15 credits), five to seven optional modules (75 to 105 credits), up to two modules (30 credits) from electives, and a research project (60 credits).

Core modules

  • Supervised Learning (15 credits)

Optional modules

Students must choose 15 credits from Option Group One and a minimum of 60 credits from Option Group Two. Students must choose a further 30 credits from either Option Group Two or approved electives.

Option Group One (choose 15 credits)

  • Graphical Models (15 credits)
  • Probabilistic and Unsupervised Learning (15 credits)

Option Group Two (choose 60 to 90 credits)

  • Advanced Deep Learning and Reinforcement Learning (15 credits)
  • Advanced Topics in Machine Learning (15 credits)
  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Machine Learning (15 credits)
  • Approximate Inference and Learning in Probabilistic Models (15 credits)
  • Bioinformatics (15 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Programming and Mathematical Methods for Machine Learning (15 credits)
  • Statistical Natural Language Programming (15 credits)

Please note: the availability and delivery of optional modules may vary, depending on your selection.

Students may select up to 30 credits from elective modules

A list of acceptable elective modules is available on the departmental website.

Dissertation/report

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

Teaching and learning

The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Further information on modules and degree structure is available on the department website: Machine Learning MSc

Careers

Graduates from this programme have an excellent employment record. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology. Students also benefit from strong corporate and academic connections within the UCL Computer Science alumni network.

Graduates have taken machine learning research degrees in domains as diverse as robotics, music, psychology, and bioinformatics at the Universities of Basel, Cambridge, Edinburgh, Nairobi, Oxford and at UCL. Graduates have also found positions with multinational companies such as BAE Systems and BAE Detica.

Recent career destinations for this degree

  • Computer Vision Engineer, ZVR
  • Data Analyst / Data Scientist, Deloitte Data Analytics Group
  • Programmatic Yield Manager and Data Analyst, eBay
  • Data Scientist, dunnhumby
  • PhD in Computer Science, UCL

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. Machine Learning 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 graduates. Similarly graduates now work in companies in Germany, Iceland, France and the US, amongst other places, in large-scale data analysis. The finance sector has also hired several graduates recently.

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

This MSc is one of the few leading Master's programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Computer Science

96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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