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
Artificial Intelligence and Machine Learning, Big Data. New technologies and ways of working are changing the way we make decisions.
This programme will take your career to the next level and develop your ability to confidently make high impact businesses decisions that are driven by data.
The programme focuses on two key areas: analysing business data, and solving business challenges analytically. Optional modules allow you to further specialise in areas such as the economic, managerial or finance aspects of the subject.
Furthermore, you will benefit from hands-on experience of a wide range of analytics software such as simulators and mathematical tools.
The programme is studied full-time over one academic year. It consists of eight taught modules and a dissertation.
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.
Business analytics students often pursue careers as consultants, researchers, managers, and analysts.
You will get hands-on experience using a wide range of tools in the course. An indicative list of the software tools is as follows:
This programme is run in cooperation with IBM.
The programme’s aim is to provide a high quality education that is both intellectually rigorous and at the forefront of management science research, relevant for problem solving and decision making by managers.
It will respond to the emergent needs of corporations and academia for professionals who are able to work with analytical tools to generate value from available Information depots and take advantage of the vast amounts of data now provided by the modern ICT and ERP systems, which underlie the operations of modern corporations.
The programme will implant understanding of the theoretical base around knowledge management and knowledge work, practical skills and experience in using analytical software tools.
It will allow future professional managers and consultants to cope with an increasingly complex and global operational environment of the modern corporation.
Completion of the programme will provide a sound foundation for those considering continuing their academic development towards a PhD degree in the management disciplines.
The programme is structured in a way that would provide students with a choice between a more quantitative intensive track of modules or a qualitative analytic (business development track) which would reflect students’ personal strengths and preferences and match future career aspirations.
The compulsory modules provide a sound foundation which builds an analytical skillset using relevant statistical and management theories, and supports the development of practical hands-on experience applying the theoretical aspects using real-world data to address corporate challenges and find solutions to actual problems.
The readings in the module will build a sound basis which would allow students to access and understand the academic literature and undertake empirical investigations in the areas of decision modelling and business development.
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.
Surrey Business School is accredited by the Association to Advance Collegiate Schools of Business (AACSB) and by the Association of MBAs (AMBA).
Visit our website for more information on fees, scholarships, postgraduate loans and other funding options to study Computer Science: Informatique at Swansea University - 'Welsh University of the Year 2017' (Times and Sunday Times Good University Guide 2017).
The MSc in Computer Science: Informatique is a Dual Degree scheme between Swansea University and Université Grenoble Alpes for computer science.
The MSc in Computer Science: Informatique Grenoble dual degree scheme is a two year programme that provides students with an opportunity to study in both Swansea, UK and Grenoble, France. One year of the Computer Science: Informatique programme students study at Swansea University and the second year of the programme students study at Université Grenoble Alpes. Upon successful completion of the programme, students will receive an M.Sc. in Advanced Computer Science from Swansea University and a Master from Université Grenoble Alpes.
- We are top in the UK for career prospects [Guardian University Guide 2018]
- 5th in the UK overall [Guardian University Guide 2018]7th in the UK for student satisfaction with 98% [National Student Survey 2016]
- We are in the UK Top 10 for teaching quality [Times & Sunday Times University Guide 2017]
- 12th in the UK overall and Top in Wales [Times & Sunday Times University Guide 2017]
- 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
- UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
- Our Project Fair allows students to present their work to local industry
- Strong links with industry
- £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)
- Top University in Wales [Times & Sunday Times University Guide 2017]
Modules on the MSc in Computer Science: Informatique may include:
Critical Systems; IT-Security: Theory and Practice; Visual Analytics; Data Science Research Methods and Seminars; Big Data and Data Mining; Data Visualization; Human Computer Interaction; Big Data and Machine Learning; Web Application Development; High Performance Computing in C/C++; Software Testing; Graphics Processor Programming; Embedded System Design; Mathematical Skills for Data Scientists; Logic in Computer Science; Computer Vision and Pattern Recognition; High-Performance Computing in C/C++; Hardware and Devices; 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, 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 our expansion, we are building the Computational Foundry on our Bay Campus for computer and mathematical sciences. This development is exciting news for Swansea Mathematics who are part of the vibrant and growing community of world-class research leaders drawn from computer and mathematical sciences.
All Computer Science courses will provide you the transferable skills and knowledge to help you take advantage of the excellent employment and career development prospects in an ever growing and changing computing and ICT industry.
94% of our Postgraduate Taught Computer Science Graduates were in professional level work or study [DLHE 14/15].
Some example job titles include:
Software Engineer: Motorola Solutions
Change Coordinator: Logica
Software Developer/Engineer: NS Technology
Workflow Developer: Irwin Mitchell
IT Developer: Crimsan Consultants
Consultant: Crimsan Consultants
Programmer: Evil Twin Artworks
Web Developer & Web Support: VSI Thinking
Software Developer: Wireless Innovations
Associate Business Application Analyst: CDC Software
Software Developer: OpenBet Technologies
Technical Support Consultant: Alterian
Programming: Rock It
Software Developer: BMJ Group
The results of the Research Excellence Framework (REF) 2014 show that Swansea Computer Science ranked 11th in the UK for percentage of world-leading research, and 1st in Wales for research excellence. 40% of our submitted research assessed as world-leading quality (4*).
Please note this programme will be undergoing some changes for the 2018/19 entry and courses may be subject to change between now and the commencement of the programme in September 2018.
This programme offers you the chance to develop a detailed understanding of the application of geographical information science (GIS) and related technologies within the field of archaeology.
The programme retains a distinctive Scottish flavour, and students will benefit from the guidance of internationally recognised staff.
The programme combines the pedigree of Edinburgh’s GIS expertise with a long-established reputation in archaeological teaching and research.
You will gain a broad understanding of the use of GIS in archaeological surveying, recording and research and will be equipped with the analytical and communication skills necessary to work in this vibrant area.
Demand for the application of GIS within archaeology is growing at an unprecedented rate, including searching for new archaeological sites, determining the societal context of existing sites and examining the interplay between successive occupations of a site.
The proven ability of our GIS graduates in employment means our programme is held in high regard by a wide range of employers.
The programme is organised into two semesters of taught courses, delivered through lectures and seminars, after which you will work towards your individual dissertation.
Compulsory courses typically will be:
In consultation with the Programme Director, you will choose from a range of option courses. We particularly recommend:
Courses are offered subject to timetabling and availability and are subject to change. Field trip
There is a field trip focusing on techniques for capturing geospatial information. This field trip has historically taken place at the Kindrogan Field Centre, Perthshire.
The expertise gained on this programme will allow you to continue to study or to pursue a career in surveying, illustration and 3D visualisation, digital archiving, heritage management, terrain modelling, database management, geomatics or consultancy.
Our GIS graduates have gained work in both public and private sector organisations, including Historic Scotland, English Heritage, the Royal Commission on the Ancient and Historical Monuments of Scotland, thinkWhere (formerly Forth Valley GIS) and CFA Archaeology.
You may also be interested in the following programmes:
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