Develop the skills you need for a career in this fast-emerging field of data science.
This programme will deepen your understanding of advanced software development, systems for big data analytics, statistical data analysis, data mining, data privacy and security, data visualisation and exploration.
It is an interdisciplinary programme, designed for students with a first degree in subjects such as:
Our teaching is strongly linked to research within the Faculty of Engineering and Informatics, which includes aspects of applied computing, theoretical computer science, and communications and networks. Statistical analysis of data across various disciplines is a central theme of our research.
You can tailor your studies to particular areas of interest or career aspirations through our range of optional modules, and in the final dissertation (which is a significant piece of project work).
On graduation, you’ll be ready and able to develop solutions to challenges in big data analytics and big data systems.
2:2 or above in computer science, computer engineering, informatics or other computer-related subjects (including management disciplines such as finance, economics, business studies etc.) from an approved degree-awarding body
Candidates who do not fulfil the normal entry requirements but have extensive industrial experience in a related area are considered on an individual basis.
English language requirements
Minimum IELTS 6.0 or equivalent
If you do not meet the IELTS requirement, you can take a University of Bradford pre-sessional English course.
What you will study
The programme is intended to equip graduates with the cutting-edge knowledge and skills to work in the industry as a Data Scientist, Big Data Architect, or Big Data Analyst.
Software Development (COS7009-B)
Big Data Systems and Analytics (COS7006-B)
Statistical Data Analysis (COS7005-B)
Data Mining (COS7028-B)
Information Theory and Data Communication (COS7007-B)
Business Systems Security (COS7035-B)
Mobile Application Development (COS7025-B)
Concurrent and Distributed Systems (COS6012-B)
Data Visualisation PG (GAV7021-B)
Learning and assessment
You'll learn through a mixture of formal lectures, practical lab sessions, tutorials and seminars.
Some modules involve supervised group work, usually with an assigned academic staff member for each group.
Most modules are related to research in the school.
All modules require students to undertake independent study, supported through distance learning technologies such as our Virtual Learning Environment. Reading lists and suggested resources for independent study provide further direction for students to undertake this work, and regular contact hours and informal feedback throughout the courses provide opportunities for further guidance for learners.
Assessments for modules mostly take the form of practical coursework, lab tests and written exams, with all forms being well represented across all modules.
Our facilities are impressive, with several laboratories filled with dual-screen, dual boot (Windows and Linux) systems packed with industry-standard software.
Our specialised labs, such as the Ethical Hacking lab and the Internet of Things lab, allow students to build their skills within these key areas of growth, in a structured way through taught modules.
We provide a range of online facilities to support independent learning, including our Virtual Learning Environment which gives you access to learning materials and collaborative learning tools 24/7, anywhere in the world. We also provide virtual server technology using in house hardware to allow students to use our operating systems remotely.
Fees, finance and scholarships
Home/EU: £8,570 per year
International: £19,890 per year
Every year we award numerous non-repayable scholarships to UK, EU and international students on the basis of academic excellence, personal circumstances or economic hardship.
The University is committed to helping students develop and enhance employability and this is an integral part of many programmes. Specialist support is available throughout the course from Career and Employability Services including help to find part-time work while studying, placements, vacation work and graduate vacancies. Students are encouraged to access this support at an early stage and to use the extensive resources on the Careers website.
Discussing options with specialist advisers helps to clarify plans by exploring options and refining skills of job-hunting. In most of our programmes, there is direct input by Career Development Advisers into the curriculum or through specially arranged workshops.
Big data is a major area for future growth and investment. As the global big data industry continues to grow year after year we continue to grow our programme and continue to produce future leaders in an exciting and rewarding field.
We have a commitment to strong pastoral care for all of our students, which includes a Personal Tutor for all students, regular contact hours for tutor groups and our supportive student service teams who are always ready to help with any questions and provide the advice that you need.
In addition to standard study support through taught sessions, our Virtual Learning Environment allows students to access resources, participate in group work and submit work from anywhere in the world 24/7.
University central services are rich with support teams to assist students with every aspect of their journey through our degree programmes. From our Career and Employability Service, through our strong Students' Union, to our professional and efficient Student Finance team, there are always friendly faces ready to support you and provide you with the answers that you need.
There is much research taking place at the Faculty of Engineering and Informatics related to this Master's programme. This includes aspects of applied computing, theoretical computer science, and communications and networks. Statistical analysis of data across various disciplines is a central theme of our research.
Teaching informed by research is at the core of this programme. Graduates leave us well prepared to pursue academic research, or industry-based research and development positions.