Our Digital Media Arts MA is taught both at the University of Brighton and at Lighthouse. The Lighthouse is a digital culture agency where a key part of its work is education and professional development (PPD). Through short technology labs and courses they help empower the digital artists and creative engineers of tomorrow.
We have developed the course in the context of Brighton’s status as one of the main centres of the media economy, adopting an interdisciplinary approach that allows you to use and develop your existing skills in an environment that encourages both innovation and high-quality production.
The course provides excellent training for artists, designers and arts professionals wishing to seek a career in the creative industries, offering expert education in the areas of interaction design, social media, programming, digital film, installation, public art and interactive art. You will learn core digital media production skills, explore a broad range of creative digital practices, and access the most up-to-date developments and critical debates in the discipline.
While our professional studio environment enables you to explore the full creative potential of digital media arts practices, we also encourage live project work so that you gain direct experience and develop valuable links to the digital media and wider cultural industries.
The course offers a suitable route and an appropriate academic grounding for PhD study, as has been evidenced by recent student progression on to PhD programs at the University of Sussex, Goldsmiths, Plymouth University and The University of Auckland in New Zealand.
The course is designed to support your individual development and creativity as an artist and producer and is based around an essential core of practice-based learning, underpinned by a programme of theoretical lecture series, artist talks, seminars, workshops, tutorials and independent study.
You will learn core digital media production skills. Specialist workshops have included processing, motion graphics and sound art.
The course supports an interdisciplinary approach that enables you to develop existing skills and experiences in an environment that encourages both innovation and high quality production. Live project work in modules throughout the course will help you gain direct experience and develop valuable links in the digital media industries and wider cultural industries.
Modules will be relevant and up-to-date in this fast changing and evolving digital climate, allowing for flexibility to expand into new areas of development. Examples of theses areas include screen based web design, social media and interactive installations and also including using data analytics, coding, programming and hacking.
You will be taught by a diverse and experienced lecturing team, all of whom are creative practitioners.
The course offers a flexible mode of study for students, either as a part-time route (two years) or full time (one year).
We encourage students to create work through the use of open source data and engaging with hacker ethics, which are concerned primarily with sharing, openness and collaboration, rather than using commercial software.
Making sure that what you learn with us is relevant, up to date and what employers are looking for is our priority, so courses are reviewed and enhanced on an ongoing basis. When you have applied to us, you’ll be told about any new developments through our applicant portal.
The Digital Media Arts MA at Brighton develops your production skills and unique artistic approach. Over the course, you will build a substantial body of digital artwork that will help you get ahead in the fast-moving and competitive new media industries.
You will create your art and design work using a range of digital technologies, producing screen-based work, interactive installations, social media interventions and soundscapes. All students produce work for the assessment show towards the end of the course.
The Digital Media Arts MA is a practical course that teaches a range of skills in digital development and design that you can apply outside of university. The course aims to empower digital artists and critical engineers of tomorrow, in exploring the creative thinking that is critical to working effectively with technology.
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