This intensive programme offers an exciting opportunity to learn from world leaders in both informatics and linguistics. Drawing from our cutting-edge research, the programme’s content covers all areas of speech and language processing, from phonetics, speech synthesis and speech recognition to natural language generation and machine translation.
This flexible programme provides research or vocational training and can be either freestanding or lead to PhD study. The modular nature of the programme allows you to tailor it to your own interests.
Taught by leading researchers from Linguistics & English Language, the Centre for Speech Technology Research and the School of Informatics, this programme combines elements of linguistics, computer science, engineering and psychology.
You will develop up-to-date knowledge of a broad range of areas in speech and language processing and gain the technical expertise and hands-on skills required to carry out research and development in this challenging interdisciplinary area.
You study two semesters of taught courses, followed by a dissertation.
Most core compulsory courses have both computational and mathematical content. A few optional courses need a stronger mathematical background. Courses in the second semester can be tailored to your own interests and abilities.
Compulsory courses:
Option courses may include:
This programme aims to equip you with the technical knowledge and practical skills required to carry out research and development in the challenging interdisciplinary arena of speech and language technology.
You will learn about state-of-the-art techniques in speech synthesis, speech recognition, natural language processing, dialogue, language generation and machine translation.
You will also learn the theory behind such technologies and gain the practical experience of working with and developing real systems based on these technologies. This programme is ideal preparation for a PhD or working in industry.
This programme will provide you with the specialised skills you need to perform research or develop technology in speech and language processing. It will also serve as a solid basis for doctoral study.
Strongly interdisciplinary in nature, the Institute for Language, Cognition and Communication (ILCC) is dedicated to both basic and applied research in the computational study of language, communication, and cognition, in both humans and machines.
As technology focuses increasingly on language-based communication tools, research into the automation of language processing has become vital. ILCC offers you the broadest research scope in the UK, and a strong computational focus.
Our primary areas of research are:
Much of our research is applied to software development, in areas as diverse as social media, assisted living, gaming and education.
You may find yourself working closely with other departments of the University, particularly the School of Philosophy, Psychology & Language Sciences.
Many of our researchers are involved in cross-disciplinary research centres; for instance:
Centre for Speech Technology Research (CSTR)
The Centre for Speech Technology Research (CSTR) is an interdisciplinary research centre linking Informatics and Linguistics. Founded in 1984, it is now one of the world's largest concentrations of researchers working in the field of language and speech processing.
CSTR is concerned with research in all areas of speech technology including speech recognition, synthesis, signal processing, acoustic phonetics, information access, multi-modal interaction and dialogue systems.
The Centre is home to state-of-the-art research facilities including specialised speech and language-orientated computer labs, a digital recording studio, perception labs and a meeting room instrumented with multiple synchronised video cameras and microphones. There is also access to high-performance computer clusters, the University storage area network, a specialist library, and many speech and language databases
Centre for Design Informatics
Data driven innovation is transforming society and the economy. In the Centre for Design Informatics, we design systems for better human data interaction, in diverse settings such as health, culture, mobility and finance. We explore design from, with, and by data: the central concern is the design of flows of data which sustain and enhance human values. Relevant technologies range from the internet of things, through blockchains, to robotics, speech recognition, data visualisation, interaction design, and social computing.
Data Science EPSRC Centre for Doctoral Training
The EPSRC Centre for Doctoral Training (CDT) in Data Science, based at the University of Edinburgh, is training a new generation of data scientists, comprising 50 PhDs over five intake years, with the technical skills and interdisciplinary awareness necessary to become R&D leaders in this emerging area.
You carry out your research within a research group under the guidance of a supervisor. You will be expected to attend seminars and meetings of relevant research groups and may also attend lectures that are relevant to your research topic. Periodic reviews of your progress will be conducted to assist with research planning.
A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
While many of our graduates pursue an academic career, others find their skills are highly sought after in the technology industry. A number of our students serve internships with large UK and international software developers, while others take up positions with major social media companies.
Accredited by the British Computer Society
Speech and language technology graduates are in demand, in areas like machine translation, document indexing and retrieval, and speech recognition. Our world-leading language and speech research staff will help you to develop the skills you need.
Our courses give you experience of how real-world projects work. We consult with big employers to ensure that you develop the skills and the personal qualities they’re looking for.
You’ll learn about the issues that matter in global business and industry. Our graduates go into academic and industrial research, the software industry, banking and finance. They work for companies such as Logica, IBM, Hewlett Packard, PWC, Vodafone, the BBC and HSBC.
Our challenge is to use computation to understand all kinds of systems: computer systems, living systems and cognitive systems. Our research areas include robotics, machine learning, speech and language processing, virtual reality, computational systems biology and software verification and testing. It’s work that makes a difference to people’s lives.
We have our own high-performance network so you can access our advanced computing facilities. There are labs for teaching smaller groups, wi-fi coverage throughout the department, and you can connect your own laptop to the network. Mobile devices and tablets are available for you to borrow for project work.
We also use specialised equipment: an immersive virtual reality facility, robotics hardware and an acoustic booth for speech processing research.
We use lectures, tutorials and group work. Assessment is by formal examinations, coursework assignments and a dissertation.
This course is suitable for school-based professionals who provide support for children with speech, language and communication needs.
It is designed for students looking to gain high level knowledge and analytical skills, share their professional experience and perspectives and access current research in their field.
Students will be aiming to raise their profile as a specialist and leader in speech, language and communication needs in the school setting.
The MSc in Speech, Language and Communication Needs in Schools is jointly run by City, University of London and UCL Institute of Education. It brings together speech and language therapists, teachers and other graduate school-based practitioners for collaborative study. The programme is designed to enable students to:
Modules are facilitated by experienced clinicians, teachers and leading researchers, using a variety of direct and interactive methods. Some modules take place in large groups supplemented by small group discussion or laboratory sessions that provide hands-on experience of statistical analyses. Specialist modules take place in small groups combining lecturing with student-led discussion and workshop activities often drawing on participants' professional experiences. Moodle, the virtual learning environment at both institutions, provides an online platform for sharing module information and interactive learning. These methods support and are supported by self-directed study.
Modules are assessed through a diverse range of assignments that may include essays, literature reviews, oral presentations, poster presentations, case studies, and data analyses. Assessments require critical evaluation of the research on key issues; selective application of theory and research to a particular setting, group or individual in the student's experience; understanding of research methods; and skills in statistical analysis.
The taught programme comprises:
Teaching takes place in three 10-week terms: autumn, spring and summer. Students will normally take one module per term part-time or two modules per term full-time.
Each module runs over 3-5 whole days, 10 evenings or 10 half days. In addition, students will be expected to spend approximately half a day a week reading around the taught sessions, preparing for discussion, or completing short exercises.
Students have up to one year to complete the research dissertation.
Core modules
Elective modules
Elective modules are chosen from many available at both institutions and timing depends on module choice. Popular electives include:
At UCL IOE:
At City, University of London:
This MSc qualification raises graduates’ profile as a specialist and leader in speech, language and communication needs in the school setting. It is an advantage for teachers and clinicians seeking higher grade specialist and managerial posts.
Graduates are also eligible to apply for a research degree (MPhil/PhD) and some research posts.
Please note that this MSc does not lead to professional qualification as a speech and language therapist or teacher.
The Applied Computing Department is a young department of modest size but is successful in attracting research funding from various sources in the UK and the EU (including industry, research councils and charitable foundations). It supports a significant range of research interest and over the last few years the number of research students has grown steadily. The Department has a history of involvement in EU framework projects. More recently, we were partners in two EU FP6 funded projects: SecurePhone and BroadWan. We have been working and collaborating with many European research institutions including The Technical University Graz, CNUCE, Pisa, Thales, Thomson, TELENOR, RAL, Salzburg, Telephonica – Spain, Atos Origin, The University of Saarbrucken – Germany, INFORMA – Italy, and ENST – France.
The main research areas of interest in the Department cover image / video processing and analysis techniques and applications; wireless mobile network technologies; and biometric-based authentications for constrained devices / environments. In image processing we mainly, but not exclusively, use wavelet transform techniques for facial feature detection and recognition, online image / video compression for constrained devices, visual speech recognition, feature detection in biomedical images, digital watermarking, content-based video indexing for biometric video databases. In the wireless networking area, our research effort focuses on convergence and integration of different wireless technologies and standards, wireless mesh technologies, intrusion detection and prevention, efficiency and stability of ad hoc networks.
Currently the Department has a number of research groups consisting of 5 research active academics, 12 PhD and 3 MSc/PhD students at various stages of their studies.
Find out more about our Department of Applied Computing on http://www.buckingham.ac.uk/appliedcomputing.
Candidates spend a considerable part of their studies undertaking supervised research, at the end of which they submit a thesis embodying the results of that research. This thesis must demonstrate familiarity with, and an understanding of the subject, its principal sources and authorities. It should display critical discrimination and a sense of proportion in evaluating evidence and the judgements of others. The subject should be dealt with in a competent and scholarly manner.
Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.
The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.
On the one hand, the Master’s in Neural Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.
On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.
See the website http://www.ru.nl/english/education/masters/neural-computing/
Why study Neural Computing at Radboud University?
- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.
- Together with the world-renowned Donders Institute, the Behavioural Science Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.
- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.
- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.
- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.
- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.
The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.
- Deep learning
Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.
-Computational framework for counterfactual predictive processing
In a recent paper we introduced a computational framework, based on causal Bayesian networks, to computationally flesh out the predictive processing processing framework in neuroscience. In this project we want to extend this to so-called counterfactually rich generative models in predictive processing. Such models encode sensorimotor contingencies, that is, they represent 'what-if' relations between actions and sensory inputs. We aim to further operationalize this account using Pearl's intervention and counterfactual semantics. In this project you will combine formal computational modelling with conceptual analysis.
- Brain Computer Interfacing
Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight and technical expertise . A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.
Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies or joined recent startups.
Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:
- PhD researcher on bio-inspired computing
- PhD researcher on neural decoding
- PhD researcher on neural information processing
- Machine learning expert in a software company
- Company founder for brain-based computer games
- Hospital-based designer of assistive technology for patients
- Policy advisor on new developments in neurotechnology
- Software developer for analysis and online visual displays of brain activity
Instead of an extended research project (45 ec) you can also choose to do a smaller (30 ec) research project plus a 15 ec internship, giving you plenty of hands-on experience with AI. We encourage students to do this internship abroad.
Data is the driving force behind today's information-based society. There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex systems.
The programme focuses on modern methods from machine learning and database management that use the power of statistics to build efficient models, make reliable predictions and optimal decisions. The programme provides students with unique skills that are among the most valued on the labour market.
The rapid development of information technologies has led to the overwhelming of society with enormous volumes of information generated by large or complex systems. Applications in IT, telecommunications, business, robotics, economics, medicine, and many other fields generate information volumes that challenge professional analysts. Models and algorithms from machine learning, data mining, statistical visualisation, computational statistics and other computer-intensive statistical methods included in the programme are designed to learn from these complex information volumes. These tools are often used to increase the efficiency and productivity of large and complex systems and also to make them smarter and more autonomous. This naturally makes these tools increasingly popular with both governmental agencies and the private sector.
The programme is designed for students who have basic knowledge of mathematics, applied mathematics, statistics and computer science and have a bachelor’s degree in one of these areas, or an engineering degree.
Most of the courses included in the programme provide students with deep theoretical knowledge and practical experience from massive amounts of laboratory work.
Students will be given the opportunity to learn:
The programme contains a wide variety of courses that students may choose from. Students willing to complement their studies with courses given at other universities have the possibility to participate in exchange studies during the third term. Our partner programmes were carefully selected in order to cover various methodological perspectives and applied areas.
During the final term of the programme, students receive help in finding a private company or a government institution where they can work towards their thesis. There they can apply their knowledge to a real problem and meet people who use advanced data analytics in practice.
Advance your career in computing in this comprehensive and challenging Master’s programme where you’ll develop high level analytical, research, strategic planning and project management skills and improve your ability to design, plan and organise technology based projects.
The Master of Computing allows you to develop the skills to undertake systematic research and solve complex applied computing problems. This programme focuses on fast developing areas of computing including networks and security, internet and intranets, interactive multimedia, data mining, adaptive business intelligence, and health informatics. Key learning objectives include designing, planning and organising technology based projects that are produced on time, to high standards, and within budget. You’ll develop your analytical, research, strategic planning, project management and interpersonal skills in undertaking this programme.
Cyber Security
Be part of the select group of people who understand both the theory and practice of cybersecurity. Specialise in this area by choosing the following courses: Enterprise Network Information Security Management, Cloud Computing, Special Topic – Cybersecurity, Research Methods, and Thesis.
IT Management
Are you an IT professional who wants to further your career? Build your understanding of IT management by selecting the following courses: Managing IT Projects, Management Approaches for the IT Professional, Information Technology, and Strategic Planning.
Networks
Learn more about data communications and networks by selecting courses like Enterprise Network Design and Management, Networks and Protocols, Enterprise Network Information Security, Mobile and Wireless Communications, as well as other courses that look at network-based applications.
Web
The development of web-based applications is a hot topic at the moment. Specialise in this area by selecting courses like Interactive Multimedia Development 1 & 2, Internet Applications to Business, Internet and Intranet Management, and Web-Based Systems.
Health Informatics
Health Informatics includes courses like Interactive Multimedia and Web-based Systems.
Game Design
Game Design is a hot-topic, and many people have great game ideas, but will they work? Does the technology support their ideas and dreams? What makes a game fun? How do you quickly create a prototype from a game idea? Get the answers to these questions and enhance your Game Design portfolio by studying courses like Entertainment Theories for Software Solutions, Software Architectures for Game Design, and Interactive Media Development.
Thesis Research Topics
Currently we are able to facilitate research for your Master’s degree thesis in the following areas.
Understanding all aspects of Human-Robot interaction: the programming that coordinates a robot’s actions with human action as well the human appreciation and trust in the robot.
At present, there are many sensors and actuators in every device – so they may become embedded in a physical reality. For robots that move around in a specific setting there is a pressing need for the development of proper methods of control and joint-action. The embedded, embodied nature of human cognition is an inspiration for this, and vice versa. Computational modelling of such tasks can give insight into the nature of human mental processing. In the Master’s specialisation in Robot Cognition you’ll learn all about the sensors, actuators and the computational modelling that connects them.
Making sense of sensor data – developing artificial perception – is no trivial task. The perception, recognition and even appreciation of sound stimuli for speech and music (i.e. auditory scene analysis) require modelling and representation at many levels and the same holds for visual object recognition and computer vision. In this area, vocal and facial expression recognition (recognition of emotion from voices and faces) is a rapidly growing application area. In the area of action and motor planning, sensorimotor integration and action, there are strong links with research at the world-renowned Donders Centre for Cognition.
At Radboud University we also look beyond the technical side of creating robots that can move, talk and interpret emotions as humans do. We believe that a robot needs to do more than simply function to its best ability. A robot that humans distrust will fail even if it is well programmed. Culture also plays a role in this; people in Japan are more open to the possibilities of robots than in, for example, the Netherlands. We will teach you how to evaluate humans’ attitudes towards a robot in order to use that information to create robots that will be accepted and trusted and therefore perform even better.
See the website http://www.ru.nl/masters/ai/robot
- We offer a great mix of technical and social aspects of robot cognition.
- This programme focuses on programming robot behaviours and evaluating them rather than building the robots themselves. We teach you to programme robots that will be used in close contact with human beings, for example in healthcare and education, rather than in industry.
- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.
- This specialisation offers plenty of room to create a programme that meets your own academic and professional interests.
- Together with the world-renowned Donders Institute, the Max Planck Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.
- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.
- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.
The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You could also cooperate with the Behavioural Science Institute and work in its Virtual Reality Laboratory, which can be used to study social interaction between humans and avatars.
An example of a possible thesis subject:
- Engaging human-robot interactions in healthcare for children and/or the elderly
Social robots are often deployed with 'special' user groups such as children and elderly people. Developing and evaluating robot behaviours for these user groups is a challenge as a proper understanding of their cognitive and social abilities is needed. Depending on the task, children for example need to be engaged and encouraged in a different way than adults do. What are effective robot behaviours and strategies to engage children and/or elderly people? How can these robot behaviours be evaluated in a proper way?
Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Philips, Siemens, Honda, Mercedes, Google. Some students have even gone on to start their own companies.
Examples of jobs that a graduate of the specialisation in Robot Cognition could get:
- PhD Researcher on Cognitive-Affective Modelling for Social Robots
- PhD Researcher on Automatic analysis of human group behaviour in the presence of robots
- PhD Researcher on Automatic analysis of affective quality of conversations in human-robot interaction
- Advisor and innovation manager in the healthcare industry
- Social robotics and affective computing for robots expressing emotions
- Developer of control algorithms for using optic flow in drones
- Advisor for start-up company on developing new uses for tactile displays
- Team member in design of emotion recognition and training for autistic children
Half of your second year consists of an internship, giving you plenty of hands-on experience. We encourage students to do this internship abroad, although this is not mandatory. We do have connections with companies abroad, for example in China, Finland and the United States.
See the website http://www.ru.nl/masters/ai/robot
This programme is studied full-time over one academic year and part-time students must study at least two taught technical modules per academic year. It consists of eight taught modules and a 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.
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 CVSSP.
The taught postgraduate Degree Programmes of the Department 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:
Intended capabilities for MSc graduates:
This programme in Mobile Media Communications aims to provide a high-quality advanced training in aspects of multimedia signal processing for audio and video content production, processing and transmission.
The programme examines ways that relevant digital data can be captured or generated, and the digital streams processed, compressed, analysed and communicated over broadcast channels, mobile networks or internet.
Along with a basis of image, video and audio processing, it provides a grounding in communications related elements that include, for example, coding, networking and data transmission. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspiration.
Key to the programme is cross-linking between signals, and delivery of audio and video content. The Programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.
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.
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.
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.
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.
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).
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:
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.
We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.
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.
The MSc Play Therapy is a new collaboration between With Kids (a Scottish charity) and the MSc Art Psychotherapy (International) at Queen Margaret University.
Recognition of Prior Learning: The Recognition of Prior Learning (RPL) encompasses the process whereby one can identify, explore and claim credit for previous certificated and/ or experiential learning. Applicants however will not be able to receive accreditation in lieu of any part of the practice placements throughout the course.
International: Where your honours degree has not been studied in English, you will be required to provide evidence of English language competence at no less than IELTS 7.0 and no individual component score below 6.0.
The MSc Play Therapy is a new collaboration between With Kids (a Scottish charity) and the MSc Art Psychotherapy (International) at Queen Margaret University.
The key purpose of the profession of play therapy is defined by British Association of Play Therapists (BAPT): “Play therapy is the dynamic process between child and play therapist in which the child explores at his or her own pace and with his or her own agenda those issues, past and current, conscious and unconscious, that are affecting the child’s life in the present. The child’s inner resources are enabled by the therapeutic alliance to bring about growth and change. Play therapy is child-centred, in which play is the primary medium and speech is the secondary medium.”
The MSc Play Therapy aims to educate the next generation of play therapists to enable them to work safely and therapeutically with complex children and families. Students will gain a thorough understanding of the fundamental inter-relatedness of the child’s physical, social and emotional world, and will develop the skills to work effectively and therapeutically to enhance emotional wellbeing and transform life chances.
Applicants should possess qualities that enable them to undertake study in an appropriate manner and at the appropriate academic level. Thus the students recruited to this course will be committed, diligent, enthusiastic and possess the skills, curiosity and drive to enhance their knowledge base.
The teaching and learning approaches used encourage you to be an independent, participative learner. These approaches will engage you in lectures, problem based learning, workshops, small group discussion, seminars, observation and skills practice. The course team aims to enable students to learn from and with others through supportive peer assessment and feedback, guided by the tutor. There are three play therapy practice placement modules where you will work directly with children and families of increasing complexity. Two modules include clinical observation of a child/ children from infanthood to adolescence. Assessment methods include case study analysis, collaborative presentation, observation analysis and play therapy practice placement portfolio. While as a postgraduate student you will predominantly be working independently, there is a strong structure for academic support. Normally, there are fewer than 20 students in the class ensuring that individuals receive excellent support and benefit from interaction with other students.
The course runs over three years part-time. Students attend the learning centre at With Kids in the east end of Glasgow one day a week over the first two years. Students will also undertake play therapy practice placement, observations and attend clinical supervision individually or in small groups. Students are expected to attend their own personal therapy for the duration of the course, and 100% attendance is expected at all elements of the MSc Play Therapy.
This course is accredited by the British Association of Play Therapists.
Clinical Skills, Process and Practice 1,2 & 3 (10 credits each)/ Developmental, Clinical and Play Therapy Theory 1 & 2 (30 credits each)/ Research Methods (30 credits)/ Clinical Project (60 credits).
Play therapists practice in many environments, including: NHS, social services, primary, secondary, further and special education, charities, private practice. They also work with people of all ages (not just children) living with a wide range of emotional or physical conditions. As of 2015 the overall majority of play therapists in the UK work in health and the voluntary sector; a significant number of them work in schools and nurseries. For further information http://www.bapt.info.
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