Dr Joy Egede stood smiling with arms clasped next to laptop with screen in background back to students' heads in foreground

Computer Science with Cyber Physical Systems MSci

Jubilee Campus, Nottingham, UK

Course overview

Cyber physical systems is an area of computer science that is growing. Our course combines computer science knowledge with specialist skills in cyber physical systems. The key topics covered will include:

  • machine learning
  • neural networks
  • cybersecurity
  • human-AI interaction 

You'll take part in a group project in year two which prepares you for designing and creating the computer systems of the future. Many projects are in collaboration with industry. Previous students have worked with Capital One, Experian, IBM and UniDays. All these companies have offices in Nottingham. This project is great for your CV and can help you make contacts ready for when you start your career.

You may recognise some of our tutors from the Computerphile YouTube series. It is this inspiring teaching that you can expect at Nottingham.

Indicative modules

Mandatory

Year 1

Database and Interfaces

Mandatory

Year 1

Fundamentals of Artificial Intelligence

Mandatory

Year 1

Introduction to Software Engineering

Mandatory

Year 1

Mathematics for Computer Scientists

Mandatory

Year 1

Mathematics for Computer Scientists 2

Mandatory

Year 1

Programming and Algorithms

Mandatory

Year 1

Programming Paradigms

Mandatory

Year 2

Algorithms, data structures and efficiency

Mandatory

Year 2

Introduction to Formal Reasoning

Mandatory

Year 2

Developing Maintainable Software

Mandatory

Year 2

Introduction to Cyber Physical Systems

Mandatory

Year 2

Languages and Computation

Mandatory

Year 2

Operating Systems and Concurrency

Mandatory

Year 2

Software Engineering Group Project

Optional

Year 2

Advanced Functional Programming

Optional

Year 2

Artificial Intelligence Methods

Optional

Year 2

C++ Programming

Optional

Year 2

Distributed Systems

Optional

Year 2

Introduction to Human Computer Interaction

Optional

Year 2

Introduction to Image Processing

Optional

Year 2

Software Specification

Mandatory

Year 3

Computer Security

Mandatory

Year 3

Cyber Physical Systems Dissertation

Mandatory

Year 3

Human-AI Interaction

Mandatory

Year 3

Machine Learning

Mandatory

Year 3

Professional Ethics in Computing

Optional

Year 3

Symbolic artificial intelligence

Optional

Year 3

Collaboration and Communication Technologies

Optional

Year 3

Collaboration and Communication Technologies Development Project

Optional

Year 3

Compilers

Optional

Year 3

Computability

Optional

Year 3

Computer Graphics

Optional

Year 3

Development Experience

Optional

Year 3

Fundamentals of Information Visualisation

Optional

Year 3

Industrial Experience

Optional

Year 3

Information Visualisation Project

Optional

Year 3

Mobile Device Programming

Optional

Year 3

Schools Experience

Optional

Year 3

Software in Society

Mandatory

Year 4

Autonomous Robotic Systems

Mandatory

Year 4

Designing Sensor-Based Systems

Mandatory

Year 4

Malware Analysis

Mandatory

Year 4

Topical Trends in Cyber Security

Optional

Year 4

Advanced Algorithms and Data Structures

Optional

Year 4

Advanced Computer Networks

Optional

Year 4

Big Data Learning and Technologies

Optional

Year 4

Development Experience

Optional

Year 4

Games

Optional

Year 4

Industrial Experience

Optional

Year 4

Linear and Discrete Optimisation

Optional

Year 4

Mixed Reality

Optional

Year 4

Group Programming Project

Optional

Year 4

Individual Research Project

Optional

Year 4

Individual Programming Project

Optional

Year 4

Programs, Proofs and Types

Optional

Year 4

Project in Advanced Algorithms and Data Structures

Optional

Year 4

Schools Experience

Optional

Year 4

Simulation and Optimisation for Decision Support

Optional

Year 4

Software Engineering Management

Optional

Year 4

Handling Uncertainty with Fuzzy Sets and Fuzzy Systems

Optional

Year 4

Schools Experience

Optional

Year 4

Data science with machine learning

Optional

Year 4

Simulation and Optimisation for Decision Support

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About modules

The above is a sample of the typical modules we offer, but is not intended to be construed or relied on as a definitive list of what might be available in any given year. This content was last updated on Tuesday 3 October 2023.

Teaching methods

  • Computer labs
  • Lectures
  • Tutorials
  • Workshops

You will be given a copy of our marking criteria which provides guidance on how your work is assessed. Your work will be marked in a timely manner and you will receive regular feedback. The pass mark for each module is 40%.

Your final degree classification will be based on marks gained for your second, third and fourth years of study. Year two is worth 20%, year three is worth 40% and year four is worth 40%.

Assessment methods

  • Coursework
  • Group project
  • Research project
  • Written exam

As a guide, one credit equals approximately 10 hours of work. You will spend around half of your time in lectures, tutorials, mentoring sessions and computer labs. The remaining time is spent in independent study. Tutorial groups are usually made up of eight students. They meet every other week during term-time. Core modules are taught by a mixture of professors, associate professors, assistant professors and teaching associates with help from PhD students and research staff.

This is a new course for 2022 entry so we don't have any graduates yet. However, we know that graduates from our other courses have worked in all types of companies and industries. Typical roles include:

  • App Developer
  • Game Developer
  • Data Analyst
  • Software Developer
  • Financial Consultant

Others choose to continue studying for a PhD.

Graduates with skills in cyber physical systems could expect to work in jobs or industries such as:

  • cyber security
  • fintech (financial technology)
  • networked systems
  • robotics and autonomous systems
  • smart product and service design and development
  • artificial Intelligence engineering

Other opportunities to help your employability

The Nottingham Internship Scheme provides a range of work experience opportunities and internships throughout the year. 

The Nottingham Advantage Award is our free scheme to boost your employability. There are over 200 extracurricular activities to choose from.

92.70% of undergraduates from the School of Computer Science secured employment or further study within 15 months of graduation. The average annual salary for these graduates was £33,082.

HESA Graduate Outcomes (2017-2021 cohorts). The Graduate Outcomes % is calculated using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.

Studying for a degree at the University of Nottingham will provide you with the type of skills and experiences that will prove invaluable in any career, whichever direction you decide to take.

Throughout your time with us, our Careers and Employability Service can work with you to improve your employability skills even further; assisting with job or course applications, searching for appropriate work experience placements and hosting events to bring you closer to a wide range of prospective employers.

Have a look at our careers page for an overview of all the employability support and opportunities that we provide to current students.

The University of Nottingham is consistently named as one of the most targeted universities by Britain’s leading graduate employers.*

*Ranked in the top ten in The Graduate Market in 2013-2020, High Fliers Research.

Undergradute student Hewan Zewdu studying in the George Green library, University Park. November 5th 2021.

Course data