Big data is becoming more and more important in fields from science to marketing, engineering, medicine and government. This Masters degree will equip you with specialist knowledge in this exciting field and allow you to explore a range of advanced topics in computer science. You’ll gain a foundation in topics like systems programming and algorithms, as well as the basics of machine learning and knowledge representation. You’ll also choose from optional modules focusing on topics like image analysis or text analytics, or broaden your approach with topics like cloud computing. As one of the few schools with expertise covering text, symbolic and scientific/numerical data analysis, we can provide a breadth of expertise to equip you with a variety of skills – and you’ll work as an integral member of one of our research groups when you develop your main project. We also have close links with the Leeds Institute for Data Analytics (LIDA) which is at the forefront of big data research. Specialist facilities You’ll benefit from world-class facilities to support your learning, including:
- a state-of the art cloud computing lab with a 10-node cluster
- a large High Performance Computing (HPC) resource consisting of several clusters which are used for all forms of predictive modelling, data analysis and simulation
- a visualisation lab including a Powerwall, benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker
- Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices
- Twin Immersion Corp CyberGloves
- rendering cluster and labs containing both Microsoft and Linux platforms, among others.
Modules include: MSc Project, Machine Learning, Big Data Systems, Data Science. Optional modules: Knowledge Representation and Reasoning, Artificial Intelligence, Data Mining and Text Analytics, Semantic Technologies and Applications, Scientific Computation, Graph Theory: Structure and Algorithms, Information Visualization.
You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
A bachelor degree with a 2:1 (hons) in computer science or a comparable subject with a substantial computing element. Relevant work experience will also be considered. We expect you to have significant programming competence and prior experience of systems development and knowledge of data structures and algorithms.
Fees and funding
No fee information has been provided for this course