Department of Computer Science,
Faculty of Engineering
This course is designed for students with a numerate background (for example a first degree in mathematics, economics, engineering, physics or chemistry) as well as graduates already working in industry.
The course focuses on managing vast amounts of information and transforming it into actionable knowledge. It teaches the key skills that are required to carry out practical analysis of the types of data sets that need to be interpreted in the modern world. These include large data sets as well as structured and unstructured data. The course makes use of techniques developed within a range of disciplines, including computer science, artificial intelligence, mathematics and statistics.
- Scalable Machine Learning
- Text Processing
- Machine Learning and Adaptive Intelligence
- Natural Language Processing
- Industrial Team Project
- Individual Data Analytics Dissertation
- Professional Issues
- Statistical Data Science in R
- Computer Security and Forensics
- Parallel Computing with Graphical Processing Units (GPUs)
- Modelling and Simulation of Natural Systems
- Network Performance Analysis
- Web Technologies
We use lectures, tutorials and group work.
Assessment is by formal examinations, coursework assignments and a dissertation.
1 year full-time
Within 3 months of starting the course I secured a graduate placement as a Technology Analyst at Barclays for after my masters, which I would not have got if I had not studied this course!
Minimum 2:1 honours degree in a numerate discipline (computer science, mathematics, economics, engineering, physics, chemistry).
English language requirements
Overall IELTS score of 6.5 with a minimum of 6.0 in each component, or equivalent.
Fees and funding
+44 114 222 1800
The course information set out here may change before you begin, particularly if you are applying significantly in advance of the start date.