5G Mobile Communications and Intelligent Embedded Systems (with an industrial placement year)
(MSc) 5G Mobile Communications and Intelligent Embedded Systems (with an industrial placement year)
Entry for 2022
FHEQ level
This course is set at Level 7 (Masters) in the national Framework for Higher Education Qualifications.
Course learning outcomes
M1. Apply a comprehensive knowledge of mathematics, statistics, natural science and engineering principles to the solution of complex problems. Much of the knowledge will be at the forefront of the particular subject of study and informed by a critical awareness of new developments and the wider context of engineering.
M2. Formulate and analyse complex problems to reach substantiated conclusions. This will involve evaluating available data using first principles of mathematics, statistics, natural science and engineering principles, and using engineering judgment to work with information that may be uncertain or incomplete, discussing the limitations of the techniques employed.
M3. Select and apply appropriate computational and analytical techniques to model complex problems, discussing the limitations of the techniques employed.
M4. Select and critically evaluate technical literature and other sources of information to solve complex problems.
M5. Design solutions for complex problems that evidence some originality and meet a combination of societal, user, business and customer needs as appropriate. This will involve consideration of applicable health and safety, diversity, inclusion, cultural, societal, environmental and commercial matters, codes of practice and industry standards.
M7. Evaluate the environmental and societal impact of solutions to complex problems (to include the entire life-cycle of a product or process) and minimise adverse impacts.
M16. Function effectively as an individual, and as a member or leader of a team. Evaluate effectiveness of own and team performance.
M17. Communicate effectively on complex engineering matters with technical and non-technical audiences, evaluating the effectiveness of the methods used.
Full-time course composition
Year | Term | Status | Module | Credits | FHEQ level |
---|---|---|---|---|---|
1 | Postgraduate Academic Year | Core | MSc Individual Project (864H1) | 60 | 7 |
Autumn Semester | Core | Advanced Digital Signal Processing (102H6) | 15 | 7 | |
Core | Internet-of-Things and Embedded System Practice (883H1) | 15 | 7 | ||
Core | Mobile Communications (826H1) | 15 | 7 | ||
Option | Advanced Electronic Systems (524H1) | 15 | 7 | ||
Cybernetics and Neural Networks (100H6) | 15 | 7 | |||
Spring Semester | Core | Reconfigurable System on Chip (822H1) | 15 | 7 | |
Core | Topics in Wireless Communications (884H1) | 15 | 7 | ||
Core | Wearable Technologies (867H1) | 15 | 7 | ||
Option | Cryptography (L.7) (860G1) | 15 | 7 | ||
Digital Signal Processing Laboratory (868H1) | 15 | 7 | |||
Image Processing (521H3) | 15 | 7 |
Please note that the University will use all reasonable endeavours to deliver courses and modules in accordance with the descriptions set out here. However, the University keeps its courses and modules under review with the aim of enhancing quality. Some changes may therefore be made to the form or content of courses or modules shown as part of the normal process of curriculum management.
The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.