This course is subject to final approval.
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.
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 Institute for Adaptive and Neural Computation (IANC) is a world-leading institute dedicated to the theoretical and empirical study of adaptive processes in both artificial and biological systems. We are one of the UK’s largest and most prestigious academic teams in these fields.
We foster world-class interdisciplinary and collaborative research bringing together a range of disciplines.
Our research falls into three areas:
In machine learning we develop probabilistic methods that find patterns and structure in data, and apply them to scientific and technological problems. Applications include areas as diverse as astronomy, health sciences and computing.
In computational neuroscience and neuroinformatics we study how the brain processes information, and analyse and interpret data from neuroscientific experiments
The focus in the computational biology area is to develop computational strategies to store, analyse and model a variety of biological data (from protein measurements to insect behavioural data).
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 in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
The research you will undertake at IANC is perfectly suited to a career in academia, where you’ll be able to use your knowledge to advance this important field. Some graduates take their skills into commercial research posts, and find success in creating systems that can be used in everyday applications.
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Data Science at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
MSc in Data Science aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students of the MSc Data Science will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the Data Science programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.
The MSc Data Science programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mine both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students of the Data Science programme will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students of the Data Science programme also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.
The MSc Data Science programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students of the Data Science programme will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.
Modules for the MSc Data Science programme include:
- Visual Analytics
- Data Science Research Methods and Seminars
- Big Data and Data Mining
- Big Data and Machine Learning
- Mathematical Skills for Data Scientists
- Data Visualization
- Human Computer Interaction
- High Performance Computing in C/C++
- Graphics Processor Programming
- Computer Vision and Pattern Recognition
- Modelling and Verification Techniques
- Operating Systems and Architectures
The Department of Computer Science is well equipped for teaching, and is continually upgrading its laboratories to ensure equipment is up-to-date – equipment is never more than three years old, and rarely more than two. Currently, our Computer Science students use three fully networked laboratories: one, running Windows; another running Linux; and a project laboratory, containing specialised equipment. These laboratories support a wide range of software, including the programming languages Java, C# and the .net framework, C, C++, Haskell and Prolog among many; integrated programme development environments such as Visual Studio and Netbeans; the widely-used Microsoft Office package; web access tools; and many special purpose software tools including graphical rendering and image manipulation tools; expert system production tools; concurrent system modelling tools; World Wide Web authoring tools; and databases.
As part of the expansion of the Department of Computer Science, we are building the Computational Foundry on our Bay Campus for computer science and mathematical science.
- Data Analyst
- Data mining Developer
- Machine Learning Developer
- Visual Analytics Developer
- Visualisation Developer
- Visual Computing Software Developer
- Database Developer
- Data Science Researcher
- Computer Vision Developer
- Medical Computing Developer
- Informatics Developer
- Software Engineer