The aim of this module is to develop student expertise in technical design, planning and management of a multi-disciplinary team engineering research focused project, providing students with an opportunity to consolidate knowledge and skills developed throughout their programme.

The aim of this module is to enable the students to act as mentors for teams that are completing projects in part B.

The aims of this module are to develop the theory and practice of multi/many-core programming in an engineering context.

More information to follow.

The aims of this module are to:

• Provide a comprehensive introduction to antennas and their functioning.
• Provide practical experience in design and measurement of antennas.

The aim of this module is to introduce the facts governing the nature, availability and characteristics of the solar resources and the fundamental concepts of photovoltaics and solar thermal conversion. The conversion technologies are examined critically in terms of design, efficiency, manufacturing options and costs.

The aims of this module are:

• To provide critical overview of statistical methods and machine learning required for analysing data.
• To develop a systematic and practical understanding of regression and classification analysis.

The aim of this module is to introduce wind energy and the fundamental concepts of wind turbine design including aerodynamics, structure and control. The economic, technical, institutional and environmental aspects of onshore and offshore wind farm development are also considered.

More information to follow.

The aims of this module are to:

• To present studies on a deep understanding of the specific digital communication technologies critical to IoT systems.
• To explore the application, strengths, and limitations of various digital communication technologies in IoT.
• To develop practical skills in designing IoT communication systems using current technologies and protocols.

The aim of the module is to develop critical understanding of the fundamentals of digital signal processing, as applied to numerous and common-place digital systems, with the use of computer simulation based tools.

The aim of this module is to develop students' critical, informed knowledge of a broad range of biomass energy technologies including combustion and anaerobic digestion.

The aims of this module are to:

• Provide an understanding of advanced electronic engineering applications.
• Provide insight into practicalities of advanced sensor systems in real world applications using underwater acoustics applications as a case study.

The aim of this module is to enhance the understanding of the principles of Radio Frequency (RF) and Microwave Integrated Circuit/System Design using CAD software simulation tools and measurement techniques.

This module aims to provide knowledge and understanding of the electrical engineering associated with renewable-energy systems, and particularly the integration of renewable-energy systems into existing electrical power systems. It is primarily intended to equip designers rather than installers. The module presents internationally applicable principles rather than country-specific regulations and practices.

The core aim of this module is to ensure students are able to take advantage of Machine Learning (ML) techniques to solve practical engineering problems. Towards that end the following aims are established:

• Provide a base understanding of Machine Learning (ML) in the wider context of Artificial Intelligence (AI).
• Establish ML approaches and algorithms.
• Explore ML techniques in practical engineering contexts.
• Establish the challenges with ML in engineering.
• Deliver ML solutions in engineering, ensuring proficient use of essential tools for practical applications.