Compulsory modules
Individual Project
More information to follow.
Engineering Management: Finance, Law and Quality
The aim of the module is to enable students to understand the financial, legal and quality management principles that apply to the operational management of engineering organisations.
Deployment of Machine Learning Inference Models in loT Devices
The aim of this module is to develop the theory and practice of deploying machine learning (ML) inference models in resource-constrained IoT devices.
Electronic System Design with FPGAs
The aim of this module is to teach students the use of Linux Server Operating Systems, toolchains (e.g., Mentor Graphics) and methodologies commonly used in digital and electronic computing system design targeting Field Programmable Gate Arrays and Systems-on-Programmable-Chips (SoPCs) domains.
Optional modules
Computer Networks
The aim of the module is to provide students with the knowledge in computer networks and security fundamentals including the network infrastructure, protocols, data confidentiality, integrity, availability and trust.
Systems Engineering Applications Theory
The aim of this module are to explore the concepts of advanced systems methods and systems integration and improve the students' confidence and ability to identify, select and apply an appropriate combination of systems methods, tools and processes to tackle systems problems in a group case study, focusing on a system problem requiring innovation and creativity in the design approach.
Embedded Systems Design and Implementation
The aim of the module is to gain knowledge and experience of real-time embedded software design and implementation.
State Space Control
The aim of the module is to provide the students with an understanding of advanced considerations related to control engineering and control implementation via computers.
Cybersecurity for Embedded Systems
The aim of this module is to develop the theory and practice of security challenges and technologies for embedded systems in an engineering context.
Digital Control
The aim of the module is to provide the students with an understanding of advanced considerations related to control engineering and control implementation via computers.
Industrial Machine Vision
The aim of the module is to introduce the student to modern digital image processing methods for image capture, enhancement, segmentation, analysis and machine vision for use in industrial applications.