Computer Systems Engineering MEng

Group Project and Engineering Skills

This module will help you develop the fundamental practical and professional skills that underpin electrical, electronic and mechatronic engineering. It will also help you develop the personal attributes essential in an engineer of any discipline. 

Five types of activities are used: —(1) lab-based activities to develop specific engineering skills and encourage the internalisation of theory;(2) an extended group project to develop an embedded system using the systems engineering approach. Students apply and develop technical and transferable skills simultaneously whilst working with partially open-ended problems; (3) address sustainability of the extended project using the UN's sustainable development goals; (4) programming skill lectures and laboratories to develop embedded programming abilities and support the extended project; and (5) a focussed, week-long, cross-faculty interdisciplinary design activity taken alongside students studying different engineering disciplines, addressing the ethical, social, economical and sustainability of solutions to engineering challenges of the 21st century. It will equip you with essential teamwork, design, problem-solving and communication skills. Particular attention will be paid to employability, sustainability, and inclusivity. Through real-life engineering projects, you will be introduced to tackling complex challenges.

The skills which you will develop include critical thinking, problem solving, adaptability in the face of unexpected challenges and professionalism. You will also develop the ability to use systems engineering approaches, to use specific pieces of hardware and software, to work effectively individually and in a group as an engineer, to approach challenges ethically and with a professional mindset, and to communicate effectively.

40 credits

Engineering Modelling and Mathematics

This module serves as an introduction to common system analysis tools and their application to simple mechatronic systems. 

You will study fundamental mathematics topics and be introduced to the first principles of modelling and system behaviour. You will focus predominantly on first-order linear systems. 

The tools you use in this module will be applied to a wide breadth of engineering applications.

20 credits

System Analysis and Machine Learning

This module is an extension of system analysis tools for application to high order, non-linear and discrete mechatronic and AI systems.

You will continue your study of fundamental, but slightly more advanced, mathematics topics. We will show you how to generalise and extend first-principles modelling and system behaviours to a broader range of systems. 

We will also introduce you to computer tools used in electrical, mechatronic and computer engineering.

20 credits

Electric and Magnetic Circuits

This module provides a comprehensive foundation in the analysis of circuits and networks, essential for any aspiring electrical engineer. You will learn both direct current (DC) and alternating current (AC) circuits, equipping you with the tools and techniques necessary to understand and solve electrical circuits and networks.

You will learn to apply fundamental circuit theorems and analysis methods to determine voltage, current, and power in various circuit configurations. We will investigate the transient and steady-state responses of first and second-order circuits, both in the time and frequency domains, providing a deep understanding of circuit dynamics. 

The second half of the module will be dedicated to magnetic circuits, including the analysis of transformers, motors, and generators, crucial components in power systems and electromechanical devices. We will discuss the interaction between electrical circuits and magnetic circuits and introduce the idea of mutual coupling and transformers. Finally, you will gain insight into the structure and operation of electrical networks, providing context for the practical application of the principles learnt throughout the module.

20 credits

Analogue and Digital Electronics

This module provides a comprehensive introduction to the fundamental principles of both digital and analogue electronics, forming the foundations for further studies in electronic engineering. We will explore the building blocks of modern electronic systems, from the logic gates that underpin digital systems to the semiconductor devices that enable analogue signal processing.

In the digital domain, you will learn Boolean algebra, apply logic manipulation techniques, and design both combinational and sequential logic networks, understanding their application in practical logic circuits. Furthermore, you will be introduced to hardware description languages (HDLs) and learn to analyse and simulate digital components and structures.

Transitioning to analogue electronics, we will introduce semiconductor materials, exploring the behaviour of diodes and semiconductor transistors. You will learn to apply circuit analysis principles to predict the behaviour of semiconductor devices in circuits. You will gain an understanding on the use of the transistor as switches and develop your ability to design and analyse transistor-based circuits. Furthermore, we will introduce operational amplifiers (op-amps), exploring their versatile applications. The module will conclude with an overview of integrated circuit manufacturing, from semiconductor boules to packaged ICs.

20 credits

Industrial and Design Projects

This module will give you the chance to apply the knowledge and skills you have acquired in your first year to engineering problems. The module has three elements: —(1) Project management approaches, taught mainly in lectures.(2) The Sheffield industrial project scheme (SHIPS) where you work on an industrial project in small groups, presenting a poster to industrial partners and your colleagues.(3) An extended design project where you apply project management and technical skills to model, design, implement and test an artefact. The list of available projects will vary from year to year, but will always encompass a range of topics from different aspects of electrical and electronic engineering.

As part of this module, you will also undertake a focussed, week-long, cross-faculty interdisciplinary design activity, aimed at equipping you with essential teamwork, design, problem-solving, and communication skills. In addition to a focus on employability, sustainability and inclusivity, you will apply more advanced engineering technical knowledge to industry-relevant, complex and interdisciplinary problems.

20 credits

Control and Communication Systems

In this module, you will learn how to model, analyse, and design both control and communication systems. You will explore how signals are represented, transmitted, received, and affected by noise, and how to calculate key performance metrics. You will also be introduced to the foundations of radio-frequency circuit analysis which is the cornerstone of modern communication architectures.  

You will also study the role of feedback in shaping dynamic system behaviour, learning to analyse stability and performance, and design controllers using classical and modern methods. Throughout the module, you will apply these concepts to practical engineering problems, integrating modelling, analysis, and design. By the end, you will have the skills to evaluate system performance, design effective solutions, and apply your knowledge to real-world communication and control challenges. 

You will gain practical experience in applying theoretical concepts in the laboratory and reporting the experimental results.

20 credits

Applied Engineering Mathematics

This module introduces advanced mathematical methods used to solve core problems in electrical, electronic, and mechatronic engineering systems.

You will learn to use mathematical techniques to analyse signals, enabling the calculation of signal power and frequency response. You will also learn to model linear systems mathematically, decomposing them into characteristic modes to calculate time evolution, determine stability conditions, and implement noise reduction strategies.

You will gain foundational skills in regression, optimisation, and probability, enabling you to develop the machine learning and artificial intelligence algorithms used in modern autonomous systems.

Finally, you will explore engineering problems in multiple dimensions through vector calculus—the natural language of fields and waves. This framework will enable you to design and analyse physical components such as transformers, transmission lines, waveguides, and semiconductor devices.

20 credits

Embedded Systems Engineering

This module covers embedded and system engineering. Systems engineering is a structured process for transforming stakeholder needs into a complete system solution through requirements analysis, design, implementation, testing and deployment. Most systems today are embedded systems and are made up of both hardware and software, underpinned by digital electronics and microcontroller-based embedded hardware. In this module, you will learn digital electronics concepts in embedded hardware and follow a software engineering approach to use them in an engineering design within a project context. 

The use of object oriented programming will be introduced, and you will write computer programs for embedded hardware. You will also study the interface between hardware and software, including how digital input/output (I/O) and common peripherals are used to connect software to real devices, and how embedded architecture affects design decisions and performance.

You will work on an embedded systems project that ties in all the concepts learnt in the module. From the outset, you will be performing system engineering inclusively, by designing and developing embedded systems in a way that is accessible, equitable and responsive to the diverse needs of users, developers and environments.

20 credits

Analogue devices and circuits

In this module you will study the underlying physics of semiconductor devices, understand how they are designed and how careful design of semiconductors results in useful circuit elements. You will cover many types of semiconductor devices such as transistors (bipolar, field effect), diodes, light-emitting diodes, lasers, photodetectors and solar cells. We will also introduce you to opto-electronics. This knowledge will enable you, in future years, to learn how to design semiconductor devices for a wide range of applications.

You will also study the use of semiconductor devices in circuits. Common circuit building blocks, such as voltage and power amplifiers, oscillators and digital logic are all implemented using different versions of the same semiconductor devices. You will learn how to analyse these circuits and design your own. You will also see how the design decisions made in silicon affect the function of a device in a circuit.

20 credits

Software and Hardware Design for AI Systems

In this module, you will learn to apply systematic strategies to solve computer-engineering problems. The module adopts two approaches. You will use traditional programming methods to learn a range of algorithmic techniques and to study the data structures needed to implement them. Second, you will study hardware description language, a form of language used to describe digital circuits, and then model and synthesise logic circuits to solve computer-engineering problems. You will learn about computer and embedded system organisation and how software  and automation engineering techniques are applied to the management of both hardware and software to manage design, testing and verification. Coursework will be used to bridge the gap between theory and practice by applying everything you've learned to a real-world AI project.

20 credits

Third year modules:

Individual Project

This module is an important project where you will demonstrate your engineering competence at bachelor level. Working individually under the supervision of a member of academic staff, you will undertake an individual project to further develop your skills and gain new project-specific knowledge through independent learning and experimentation. To do this, you will need to draw on all the skills, knowledge and experience you have acquired during your studies. 

As part of the project, you will undertake a critical evaluation of technical literature, plan and manage time and resources in your project and convey the results to an audience using a combination of written and non-written techniques appropriate to the background of the audience.

Alongside your project, you will learn the fundamentals of engineering management, finance, law and the commercial context in which industrial projects sit.

40 credits

Electronic and Photonic Devices

This module provides the foundation and technological understanding of electronic, semiconductor and photonic devices. Knowledge from this module underpins the rapid progress in computing, data centers, high speed communication and electrical machines. 

This module will prepare you for work in the electronic industry (which is a very large industry), to pursue advanced courses in electronics and to enable you to contribute to rapidly developing electronic technologies.  Specifically, you will learn the key device technologies for the fields of  computing, photonics, RF and power electronics. This includes the understanding of how 1) the basic pn junction can be transformed into high efficiency solar cells to generate green energy. 2) compound semiconductors are used to create optical light sources and detectors which transmit high volumes of data through optical fibres3) transistor scaling and novel design to increase the computing power and memory4) wide bandgap semiconductors increase the current and voltage limits of transistors used in electrical machine drives5) advances in semiconductor fabrication lead to very high speed devices for RF applications.

20 credits

Digital Signal Processing

Digital signal processing (DSP) is a fundamental discipline at the intersection of mathematics, engineering and computer science that deals with the manipulation, analysis, and interpretation of signals represented in digital form. These signals can be derived from various sources such as audio, video, images, sensor data, and communication systems. At its core, DSP involves the transformation of analog signals into digital representations through a process called sampling. Once in digital form, signals can be processed, analysed, and modified using a variety of algorithms and techniques. DSP plays a crucial role in a wide range of applications including telecommunications, audio and video processing, medical imaging, radar systems and control systems.

In this module you will learn the principles of discrete-time sampled systems, including difference equations and stability. You will learn to describe digital signals and systems in different domains (e.g. time, frequency and z domains) and use a range of methods to determine the output of a digital system for a given digital input. The concept of transforms, including the fast Fourier transform (FFT), will be introduced to you. Building on these core principles, digital filter design for finite and infinite impulse response (i.e., FIR and IIR) filters and their applications are addressed, before moving on to practical implementation and testing of DSP systems. You will learn both software and hardware based implementations and their limitations. The module concludes with a look at the extension of the core principles to 2D digital signals, i.e. image processing.

20 credits

Integrated Electronic and Semiconductor Systems

This module focuses on the design and implementation of complete electronic and semiconductor system hardware, connecting system-level design to practical realisation. 

You will study digital, analogue, and how to integrate embedded software. Analogue electronics skills will be delivered with a strong emphasis on power electronics, including DC-DC and DC-AC converters. This will also serve as background to support engineering of high-voltage high-current energy, generations and motor systems. The module combines circuit analysis, practical implementation techniques, and laboratory experience.

For microelectronics and sensor systems you will examine power delivery, energy management alongside sensor integration, data conversion and communication required to build complete embedded communication control or sensing platforms. Implementation strategies for microelectronic and integrated semiconductor systems will be covered, including grounding, power distribution and EMI control. You will evaluate trade-offs between efficiency, accuracy, cost, reliability, and security, while considering safety standards and system lifetime requirements.Overall, this module develops the skills needed to design secure, reliable, and efficient electronic systems, preparing you for advanced study or professional engineering practice.

20 credits

Computer and AI System Architecture

This module introduces the architecture of modern cloud, embedded and integrated computer systems. Students will explore the anatomy of computing platforms spanning processors, memory hierarchies, peripherals, and interconnects, together with the software stack, applications and operating system that manages them. A practical understanding of the Linux operating system is developed, including boot processes, device drivers, scheduling, and memory management.

Students will apply benchmarking and profiling techniques to embedded applications and AI model, learning how architectural choices influence performance, energy consumption, and responsiveness. The module introduces hardware and software security concepts, including trusted boot, privilege levels, isolation, and attack surfaces, establishing security as an architectural concern rather than an afterthought. Emphasis is placed on system-level reasoning and quantitative evaluation, preparing students for advanced modules in safe, secure, and AI-enabled system architecture.

Through Practical coursework Build, implementation, optimisation, deployment and lifecycle management strategies for programmable software and configurable hardware systems.

20 credits

Fourth year core modules:

Group Project

The project, performed under the supervision of either two academic supervisors, or one academic supervisor and one second external marker from an industrial partner, takes the form of a multidisciplinary investigative or design project usually with a significant industrial input. Students are divided into multidisciplinary teams and presened with the project brief by the industrialists involved. Project activities are based in the research labs of the supervisor(s) although students may also have to make use of the facilities, normally within the Department. Students hold regular minuted progress management meetings with group members rotating their group management responsibilities.

45 credits

- Advanced Computer and Electronic System Architecture
- Advanced Integrated Electronics
- Verification and Test of Secure Microelectronics
- Resilient Microelectronic and Computing Systems

Fourth year optional modules:

- Semiconductor Technologies for Computing
- Power and RF Semiconductor Devices

Third year core modules:

Individual Project

This module is an important project where you will demonstrate your engineering competence at bachelor level. Working individually under the supervision of a member of academic staff, you will undertake an individual project to further develop your skills and gain new project-specific knowledge through independent learning and experimentation. To do this, you will need to draw on all the skills, knowledge and experience you have acquired during your studies. 

As part of the project, you will undertake a critical evaluation of technical literature, plan and manage time and resources in your project and convey the results to an audience using a combination of written and non-written techniques appropriate to the background of the audience.

Alongside your project, you will learn the fundamentals of engineering management, finance, law and the commercial context in which industrial projects sit.

40 credits

Machine Learning and Optimisation

Machine learning is a component of artificial intelligence that enables a computer to learn how to perform a task from data or simulations rather than being explicitly programmed for every possible scenario. Machine learning is currently being applied in a wide array of technology sectors, including robotics and autonomous systems, healthcare, bioinformatics and finance, and has experienced a huge growth in industry in recent years.  

In the first semester, the focus is on the theory and geometry of convex optimisation. You will study objective function properties, constrained and unconstrained search, and techniques for transforming complex constraints into manageable mathematical forms. In the second semester, the focus moves to the machine learning pipeline, where you will study optimisation-driven model identification and the problem of achieving good generalisation on unseen data. You will conclude the module with an analysis of the ethical issues and mitigation strategies arising from training and deploying machine learning systems.

You will study through a combination of lectures, computational laboratories, and project work, implementing optimisation and machine learning algorithms using industry-standard software, and developing practical skills needed for research and industrial environments.

20 credits

Computer and AI System Architecture

This module introduces the architecture of modern cloud, embedded and integrated computer systems. Students will explore the anatomy of computing platforms spanning processors, memory hierarchies, peripherals, and interconnects, together with the software stack, applications and operating system that manages them. A practical understanding of the Linux operating system is developed, including boot processes, device drivers, scheduling, and memory management.

Students will apply benchmarking and profiling techniques to embedded applications and AI model, learning how architectural choices influence performance, energy consumption, and responsiveness. The module introduces hardware and software security concepts, including trusted boot, privilege levels, isolation, and attack surfaces, establishing security as an architectural concern rather than an afterthought. Emphasis is placed on system-level reasoning and quantitative evaluation, preparing students for advanced modules in safe, secure, and AI-enabled system architecture.

Through Practical coursework Build, implementation, optimisation, deployment and lifecycle management strategies for programmable software and configurable hardware systems.

20 credits

Third year optional modules:

Control Systems Design

In this module, we will show you how to design, implement and evaluate modern control systems from start to finish. You will explore how to model and analyse dynamic systems using both first-principles and data-driven approaches, and how to identify system behaviour when models are imperfect. We'll introduce state feedback, observers, and Kalman filtering to help you estimate system states in the presence of noise and uncertainty. You will then learn to design advanced controllers, including linear quadratic regulators and linear model predictive control, and test them in both simulation and on a real system using hardware-in-the-loop setups. 

Throughout, we will emphasise responsible engineering practice, including considerations of safety, efficiency, resource use and environmental impact. By the end of the module, you will have the skills and confidence to take a control concept from theory through to real-world implementation and evaluation, considering both technical performance and sustainability.

20 credits

Digital Signal Processing

Digital signal processing (DSP) is a fundamental discipline at the intersection of mathematics, engineering and computer science that deals with the manipulation, analysis, and interpretation of signals represented in digital form. These signals can be derived from various sources such as audio, video, images, sensor data, and communication systems. At its core, DSP involves the transformation of analog signals into digital representations through a process called sampling. Once in digital form, signals can be processed, analysed, and modified using a variety of algorithms and techniques. DSP plays a crucial role in a wide range of applications including telecommunications, audio and video processing, medical imaging, radar systems and control systems.

In this module you will learn the principles of discrete-time sampled systems, including difference equations and stability. You will learn to describe digital signals and systems in different domains (e.g. time, frequency and z domains) and use a range of methods to determine the output of a digital system for a given digital input. The concept of transforms, including the fast Fourier transform (FFT), will be introduced to you. Building on these core principles, digital filter design for finite and infinite impulse response (i.e., FIR and IIR) filters and their applications are addressed, before moving on to practical implementation and testing of DSP systems. You will learn both software and hardware based implementations and their limitations. The module concludes with a look at the extension of the core principles to 2D digital signals, i.e. image processing.

20 credits

Integrated Electronic and Semiconductor Systems

This module focuses on the design and implementation of complete electronic and semiconductor system hardware, connecting system-level design to practical realisation. 

You will study digital, analogue, and how to integrate embedded software. Analogue electronics skills will be delivered with a strong emphasis on power electronics, including DC-DC and DC-AC converters. This will also serve as background to support engineering of high-voltage high-current energy, generations and motor systems. The module combines circuit analysis, practical implementation techniques, and laboratory experience.

For microelectronics and sensor systems you will examine power delivery, energy management alongside sensor integration, data conversion and communication required to build complete embedded communication control or sensing platforms. Implementation strategies for microelectronic and integrated semiconductor systems will be covered, including grounding, power distribution and EMI control. You will evaluate trade-offs between efficiency, accuracy, cost, reliability, and security, while considering safety standards and system lifetime requirements.Overall, this module develops the skills needed to design secure, reliable, and efficient electronic systems, preparing you for advanced study or professional engineering practice.

20 credits

Fourth year core modules (needs updating):

Group Project

The project, performed under the supervision of either two academic supervisors, or one academic supervisor and one second external marker from an industrial partner, takes the form of a multidisciplinary investigative or design project usually with a significant industrial input. Students are divided into multidisciplinary teams and presened with the project brief by the industrialists involved. Project activities are based in the research labs of the supervisor(s) although students may also have to make use of the facilities, normally within the Department. Students hold regular minuted progress management meetings with group members rotating their group management responsibilities.

45 credits

- Deep Learning for Engineering
- Advanced Computer and Electronic System Architecture
- Reinforcement Learning

Fourth year optional modules:

Natural Language Processing

This module provides an introduction to the field of computer processing of written natural language, known as Natural Language Processing (NLP). We will cover core concepts, models and algorithms for analysing and processing natural language data, exploring a range of approaches used in contemporary NLP systems, and discussing their strengths, limitations, and applications.

15 credits

Data Science with Python

This module starts with a rapid review of basic background mathematics and statistics, and an introduction to Python. The module will then introduce students to a range of statistical and programming techniques and give practice in their implementation and interpretation using Python. It aims to help students develop the knowledge and experience to select and use appropriate techniques for a variety of problems. The emphasis will be on practical application of techniques and knowledge of their scope rather than development of theoretical underpinnings. Areas to be covered include: exploratory data analysis, simple checks on data, statistical data modelling, programming and optimization. Students will also learn the fundamentals of robust data management and reproducible scientific analysis.

15 credits

Industrial Training Programme in Artificial Intelligence for Engineering

This unit will provide an insight into AI-based systems for engineering applications via industry-relevant project work. This will often be in direct collaboration with an industrial partner/external party. The industrial partner will pose a real technical challenge, and student groups will undertake both practical and computational/mathematical work to develop a solution to the engineering challenge. The work will result in a report and presentation that will also require an in-depth literature review. To supplement the main technical challenge, focused technical seminars on relevant topics will be delivered by academic staff, often in collaboration with industry. Aspects of systems engineering and project management will also be delivered to support project completion. 

15 credits

Machine Vision

The module gives knowledge of machine vision methods for a broad range of applications. It introduces you to image and video processing models and methods and provides you with skills on how to embed them in autonomous systems. You will be able to apply the acquired knowledge to both industrial and research areas.

15 credits

The Ethics of Artificial Intelligence

This module introduces students to the ethical challenges posed by computer technology with a particular focus on Artificial Intelligence (AI), encouraging critical reflection on the societal impacts of AI systems. Students will explore issues such as bias, fairness, transparency, privacy, accountability, and the implications of automation, drawing on real-world case studies and philosophical frameworks. The aim is to equip students with the tools to assess the ethical dimensions of AI technologies, engage with current debates in AI governance, and develop informed, responsible perspectives for future work in AI-related fields.

15 credits