Big Data Science and Technology
MSc
- Duration
- Start date
- Location
Suitable for applications.
Please note: We are no longer able to accept applications from international students for the September 2024 intake of this course. You are welcome to apply for the January 2025 intake. Home students can still apply for September 2024.
Overview
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:
- Computer Science
- Electrical Engineering
- Mathematics
- Physics
- Economics
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.
All of our computer science students are automatically enrolled as student members of the British Computer Society (BCS).
Professional accreditation
Accredited by BCS, The Chartered Institute for IT for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.
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.
Study support
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.
Research
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.