This course aims to equip graduates with a deep knowledge and understanding of the design tools for modern computational products and systems. Graduates specializing in fundamental theory and applications relating to the generation, distribution, analysis, and use of information in engineering and science.
We are in the next Industrial Revolution and the challenge faced by graduates is to succeed in an age of automation. There is no aspect of modern life that is now not altered by information processing engines. Examples include teaching (online learning and assessment), automotive (driverless cars and electronic control systems), the economy (high speed automated trading), entertainment and shopping (virtual assistants and recommendation engines), health (automated diagnostics and non-invasive body scanning) and the digital humanities.
The principles enabling the design of this new wave of products are embodied in the discipline of Information Engineering. This course aims to equip graduates with a deep knowledge and understanding of the design tools for modern computational products and systems. Graduates specializing in fundamental theory and applications relating to the generation, distribution, analysis, and use of information in engineering and science.
The M.Sc.is a 1-year 90ECTS course consisting of taught modules (50 ECTS) and a substantial research project (40 ECTS). In the first semester, students take modules worth at least 25 credits while in the second semester they take the balance of the credits. (Part-time students are required to take 50 credits of taught modules in the first year and the research dissertation in the second year.)
All candidates are required to take the following modules:
- Research Project/Dissertation (40 credits)
- Research Methods (15 credits)
- Statistical Signal Processing (5 credits – Semester 1)
- Introduction to Deep Learning (10 credits - Semester 1)
In addition, candidates select a further 20 credits from the following list of options to bring their total credits to 90:
- Speech and Audio Engineering (5 credits - Semester 1)
- Advanced Medical Imaging (5 credits - Semester 1)
- Audio Production Engineering (5 credits - Semester 1)
- Spatial Audio (5 credits - Semester 2)
- Motion Picture Engineering (10 credits - Semester 2)
- Wireless Networks and Communications (5 credits - Semester 2)
- Complex Systems Science (5 credits - Semester 2)
- Audio Production Techniques (5 credits - Semester 2)
- Reconfigurable Hardware for Computational Engineering (10 credits - Semester 2)
Some of the module options in either semester may be withdrawn from time to time and some new modules may be added, subject to demand.
This course can be taken full-time over one year or part-time over two years. Admission is normally restricted to graduates who have achieved an upper second class honors degree (2.1), or better, in engineering, science, computing, statistics, mathematics or a related discipline. Well-qualified candidates or industry professionals from other numerate disciplines who have sufficient knowledge of computational aspects of engineering and science may also be considered for admissions purposes subject to the decision of the Dean of Graduate Studies. We will also accept official MOOC certification from reputed online sources e.g. Coursera, eDX, the IET, the IEEE in relevant numerate topics as the appropriate demonstration of pre-requisite knowledge. Information on fees for the coming year can be found here.
The pass mark for all elements is 50%. The overall mark for the course is the credit-weighted average of the mark awarded for each module. To pass the taught modules students must achieve an overall average mark on taught modules of at least 50% and either a) pass taught modules amounting to 50 ECTS credits or b) pass taught modules amounting to at least 40 ECTS credits and achieve a minimum mark of 40% in any failed module. There are no supplemental examinations or re-assessments. To qualify for the award of the MSc degree, students must submit a dissertation and achieve a pass mark in both the dissertation and the taught modules. Students who do not pass the taught modules will not be allowed to submit a dissertation but may be eligible for the postgraduate diploma.
In order to qualify for a Masters with Distinction, students must as a minimum a) pass all taught modules, b) achieve a final overall average mark for the course of at least 70% and c) achieve a mark of at least 70% in the dissertation.
This school offers programs in:
Last updated October 19, 2018