Everything you need to know...
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What is the fee?
Home: See fees section below
International/EU: £17,155 per year -
How long will I study?
4/5 Years
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Where will I study?
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What are the entry requirements?
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What is the UCAS code?
AA17
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When do I start?
September 2025
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Placement year available?
Yes
Course summary
- Develop artificial intelligence (AI) systems to solve complex problems
- Use machine learning (ML) to support decision making
- Design and build complex software and hardware robotic solutions
- Work with companies to solve real-world practical challenges
- Access to industry-standard facilities and technology
Through practice-based learning, you’ll develop a deep understanding of how AI and robotics are brought together to create the autonomous devices found in the industries of our modern world. You’ll become a practitioner who can build smart robotic devices – and create new ones – all the while understanding the responsibility and ethical considerations the convergence of AI and robotics requires.
If you don't meet the entry requirements for our BA (Hons) course, or you’d like extra preparation before starting degree-level study, we recommend you join the foundation year.

Come to an open day
Visit us to learn more about our gold-rated teaching and why we were awarded the highest possible rating in the Teaching Excellence Framework.
How you learn
The combination of learning methods across the course allows you to develop your programming and electrical engineering skills as well as your wider professional skills – through problem-solving activities, practical implementation, and teamwork. These allow you to take an active approach to learning and self-development.
You learn through:
- Lectures
- Hands-on lab sessions and tutorials
- Regular feedback
- Teamwork and group-based learning
- Applied learning
- Discussions
- Self-study
You’ll be taught by experts from both Computer Science and Engineering disciplines, that builds into the cross-disciplinary course area, alongside experts who routinely hybridise the subject areas.
Key themes
You’ll build your understanding of how and when to use appropriate processes, tools, technologies and practices. You’ll develop programming skills which form the basis of key computer science topics – including algorithms and data structures. These feed into learning, creation and development of machine learning and artificial techniques that can be adapted and tailored for domain-specific problems.
These fundamental skills are further strengthened by introducing you to real-world projects, where you’ll deepen your understanding of the design and development of embedded systems.
Then in your final year, you’ll complete your own project that converges AI and robotic technologies – giving you the freedom to explore, research and apply new skills as you create a smart autonomous device you can be proud of.
Course support
You will be supported in your learning journey towards highly-skilled, graduate-level employment through a number of key areas. These include:
- Access to specialist support services to help with your personal, academic and career development
- Access to our Skills Centre with one to ones, webinars and online resources, where you can get help with planning and structuring your assignments
- Industry-specific employability activities such as live projects, learning in simulated environments and networking opportunities
Course leaders and tutors

Michael Meredith
Associate Head in the School of Computing and Digital TechnologiesMichael is a Principal Lecturer on the BSc Computer Science degree at Sheffield Hallam University, were he teaches programming, computer architecture and practical a … Read more

Tim Spencer
Research FellowTim's research at MERI involves the application of theory and simulation techniques for the predictive modelling of real life systems that involve fluids.
Applied learning
Work placements
You’ll have the opportunity to complete a year-long work placement before your final year. This helps you gain personal and professional skills through real-world experience – as well as an Applied Professional Diploma in addition to your degree, further enhancing your graduate profile.
On placement you’ll apply the knowledge and skills you’ve gained on your course – in areas such as embedded systems, machine learning, artificial intelligence, software design and electrical engineering solutions.
You’ll also be supported to take advantage of work experience opportunities throughout your course, through access to a range of support activities, resources and employer events from our Employability Team. These will further add to your employability skillset, confidence and opportunity-awareness – helping you to succeed in your career after graduating.
Live projects
Tackling problems in industry helps you prepare for a career by tackling challenges and complex problems that meet a combination of societal, user, business and customer needs – while also considering ethical, diversity and safety demands.
In your first and second years you’ll work on real client-based projects. After analysing their requirements, you’ll design, implement and test a prototype which you’ll present back to key stakeholders. This is great experience of the demands you’ll face when you graduate – and a confidence boost while you’re applying for work placements.
Networking opportunities
Employers and industry practitioners are an influential part of the design, content and teaching of the course. Alongside the placement opportunities and live projects you complete, your future career is supported by the frequent involvement of employers and IT professionals, through, for example, guest lectures and employer fairs.
Future careers
This course prepares you for the following career pathways:
- Artificial intelligence and machine learning research and development
- Robotics engineering
- Embedded systems engineering
- Software development
- Electrical engineering
Where will I study?
You study at City Campus through a structured mix of lectures, seminars and practical sessions as well as access to digital and online resources to support your learning.
City Campus
City Campus is located in the heart of Sheffield, within minutes of the train and bus stations.
City Campus map | City Campus tour

Adsetts library
Adsetts Library is located on our City Campus. It's open 24 hours a day, every day.
Learn moreEquipment and facilities
On this course you work with:
- Industry-standard software tools and hardware devices
- Embedded Systems including IoT and SBC devices
- A robotics and automation laboratory
Media Gallery
Entry requirements
All students
UCAS points
- 80
This must include at least 32 points from one A level or equivalent BTEC qualifications. For example:
- CDD at A Level.
- MMP in BTEC Extended Diploma.
- Pass overall from a T level qualification with C from core
- A combination of qualifications, which may include a maximum of one AS level, EPQ and general studies
You can find information on making sense of UCAS tariff points here and use the UCAS tariff calculator to work out your points.
GCSE
- English Language at grade C or 4
- Maths at grade C or 4
- Science at grade C or 4
*GCSE Equivalents
- Level 2 Literacy or Functional Skills Level 2 English
- Level 2 Numeracy or Functional Skills Level 2 Maths
• Access - an Access to HE Diploma with at least 45 credits at level 3 and 15 credits at level 2. At least 15 level 3 credits must be at merit grade or above from a QAA-recognised Access to HE course, or an equivalent Access to HE certificate.
We may also accept you, if you have no formal qualifications but can show evidence of ability and a genuine commitment to studying the subject.
Some applicants may be invited to attend an informal interview with the course leader to ensure that the programme is suitable for themselves and their aspirations.
UK students may be able to claim financial support for the course.
If English is not your first language, you will need an IELTS score of 6.0 with a minimum of 5.5 in all skills, or equivalent. If your English language skill is currently below IELTS 6.0 we recommend you consider a Sheffield Hallam University Pre-sessional English course which will enable you to achieve an equivalent English score.
Additional information for EU/International students
If you are an International or non-UK European student, you can find out more about the country specific qualifications we accept on our international qualifications page.
For details of English language entry requirements (IELTS), please see the information for 'All students'.
Modules
Important notice: The structure of this course is periodically reviewed and enhanced to provide the best possible learning experience for our students and ensure ongoing compliance with any professional, statutory and regulatory body standards. Module structure, content, delivery and assessment may change, but we expect the focus of the course and the learning outcomes to remain as described above. Following any changes, updated module information will be published on this page.
You will be able to complete a placement year as part of this course. See the modules table below for further information.
Year 1
Compulsory modules
This module supports and broadens your learning through practical experiments and application of mathematical knowledge. As an engineer or mathematician you’ll need to develop a variety of experimental and transferable skills as part of your education and ongoing professional development.
You’ll study topics such as:
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Mechanical laboratory experiments
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Electrical and electronic practical work and skills
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Mathematical case studies with real-world problems
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Town planning and traffic management
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Monitoring natural phenomena
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How to design experiments
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How to deal with experimental errors
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Scientific writing
This module introduces you to core topics in science, physics and mathematics. You’ll develop an awareness of mathematics contexts and your ability to apply mathematics appropriately.
You’ll study topics such as:
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Numbers and order of operations
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Algebra, mathematical functions and solving simple equations
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Geometry including trigonometry of right-angled triangles
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Vector addition and resolution
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Technology for calculations and plot graphs
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Ohm's Law and capacitance
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LR, CR and LCR circuits
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AC theory
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SI units and motion in a straight line (rectilinear)
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Forces, friction and equilibrium
This module consolidates your previous learning, developing further essential skills in science, physics and mathematics. You’ll study mathematical, electrical and mechanical areas of the subject with a structured approach to problem solving.
You’ll study topics such as:
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Functions and product, quotient, chain rules, gradients, min/max problems
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Integration by function, parts, substitution and integrals
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Velocity and acceleration problems
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Trigonometric graphs, equations and sine/cosine rules
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Logarithmic and exponential functions and graphs
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Inverse and simultaneous equations using matrices
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Electronics for measurement, diodes, power supplies and sensors
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Op amps, analogue to digital converters and microcontrollers
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Circular motion, work, energy, power and simple harmonic motion
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Specific and latent heat, changes of state, expansion/contraction
This module studies the physical and chemical principles underpinning materials science, introducing the structure, processing and characteristics of engineering materials. You’ll explore different manufacturing techniques, associated equipment and tooling, while developing your presentation and information skills.
You’ll study topics such as:
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Atomic and electronic structure of atoms
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Chemical reactivity and electronic structure
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Ionic bonding, crystals, compounds and covalent bonding
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Characteristics and examples of organic compounds
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Metallic bonding and conservation of mass in chemical reactions
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Metals, organic polymers, ceramics and composites
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Health, safety and solidification processes
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Hot and cold metal working processes
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Ceramic and polymer processing
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Machining processes
Year 2
Compulsory modules
Module Aim:
To develop a foundation for the understanding and familiarisation of basic analogue and digital electronic components, systems and their applications and to introduce their applications.
You will study topics such as:
- Digital electronics
- Mathematics for digital electronics
- Digital electronic circuit components
- Circuit design methods
- Digital components and circuits
- Software packages for digital circuit design
- Analogue electronics
- Analogue electronics key basic components
- Analogue circuit concepts and signals
- Measurement and testing techniques
- Non-linear electronic devices principles and applications
Module Aim:
This module is intended to teach mathematical methods and the basics of computer programming, using a structured approach to mathematical techniques, programming and appropriate software tools, thus enabling students to produce mathematical and programming solutions for a range of simple engineering problems.
Module Delivery:
This module will be delivered via a mixture of lectures, seminars / tutorials, and laboratory sessions.
Indicative Content:
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Software development processes and tools. number systems and character coding
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Primitive data types and data structures, variable declaration and initialisation
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Basic arithmetic and logical expressions
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Basic programming constructs, such as; selection and iteration
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Creation of functions, arrays, pass by value and reference arguments.
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Relevant language specific features and applications,
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Solving/manipulating equations involving elementary functions (polynomials, trigonometric, exponential, logarithmic).
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Differentiation, integration, and applications.
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Complex numbers and applications.
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Matrices and solving systems of linear equations.
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Analytical solutions of 1st and 2nd order ODEs.
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Software-based solution verification e.g. MATLAB
This module will be delivered through design challenges such as IET Global Challenge, Engineers without Borders, etc as an applied project using blended approaches. This gives the students an opportunity to recognise and engage with professional behaviours and roles that consider inclusivity and industry sector values and give them a chance to express their own values. Students will work collaboratively in teams to explore real-world challenges and professional roles. The Engineers Without Borders’ “Engineering for People” design project for example will give students the opportunity to apply their knowledge of electronics, develop team working and leadership skills and apply their knowledge of CAD software and lab equipment. Students will reflect on their own strengths, recognise their professional behaviours, limitations, and experiences from Engineers Without Borders’ “Engineering for People” design project to support their future preparation for a recruitment and placement.
Indicative Content:
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Safe working practices, relevant codes of practice (including risk and environmental issues) and safety standards.
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Engineering processes (e.g. using hand and tools, test equipment, soldering, fabrication, and measurements).
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Design and development tools, with appreciation of their limitations and applicability.
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Computer based design tools (e.g. Solidworks, Eagle CAD, simulation tools, etc).
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Sketching and interpretation of engineering drawings and electrical/electronic circuit diagrams.
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Design, building, testing and modification of appropriate artefacts to meet the requirement of an external body or competition, such as IET Global Challenge, Engineers without Borders, etc.
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Report writing, team working, oral presentations.
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Professional and personal development planning.
This module introduces computer programming. It will develop your understanding of practical programming concepts and their deployment in a mainstream object-oriented programming language through the creation of code and applications.
You’ll study topics such as:
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Problem solving, top-down design and functional decomposition
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The development process - specification, design, implementation, testing.
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Variables, data types, and data structures
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Algorithms and control structures
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Object-oriented programming
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Program quality
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Software tools and integrated development environments (IDEs)
Year 3
Compulsory modules
This module will continue to build your programming knowledge, looking at object-oriented programming in a modern programming language such as C/C++. It will introduce manual dynamic memory management and discuss heap and stack memory alongside profiling. You will practice more advanced aspects of programming languages and develop an understanding of design patterns and standard software libraries.
You’ll study topics such as:
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Object-oriented principles, concepts and design: encapsulation, inheritance, polymorphism
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Abstract and interface classes
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Dynamic memory management
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Memory pointers and references
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Memory profiling
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Standard template libraries (STLs)
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Operator overloading
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Templates / generics
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Event-based coding
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Design patterns
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Tool support for OO development
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Version control software
Aims:
This module will impart key concepts in computer science to students and to further develop important skills in computer-based problem solving and data manipulation.
Indicative Content
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Introduction to algorithms (role and importance of algorithms in computer science). Concurrent, and parallel algorithms
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Sorting algorithms (merge sort, heap sort, quick sort)
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Searching algorithms
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Linked lists (Singly linked lists; double linked lists)
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Stacks and Queues
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Recursion
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Tree structures (creating, searching, traversing, merging).
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Graph structures (traversals, activity networks, critical paths, shortest paths)
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The theory of algorithms (Big-O notation, Computability; Turing machines).
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Complexity (computational and control flow).
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Optimisation problems (Travelling Salesman Problem, Bin Packing).
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Optimisation search methods (Genetic algorithm, Hill Climbing, Simulated Annealing, Tabu search algorithm, Iterated Local Search).
This module delivers knowledge and practical skills of machine learning algorithms for artificial intelligence applications. It will present the key mathematical principles and concepts required to create machine learning algorithms through data-driven approaches. You will gain practical experience while designing, implementing, and evaluating machine learning systems to solve real-world artificial intelligence problems.
You’ll study topics such as:
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Data-driven approaches to machine learning
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Linear regression and gradient descent
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Regression and classification problems
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Machine learning algorithms: decision trees, support vector machines, ensemble learning and k-mean/mean-shift clustering
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Data pre-processing, cleansing and feature extraction
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Evaluating machine learning system by using cross-validation, confusion matrix and receiver operating characteristic
Module Aim:
This module, through an applied project, will provide students with the knowledge and skills necessary to design and develop engineering solutions that meet a combination of societal, user, business and customer needs.
Students learn to apply an integrated or systems approach to complex problems, evaluate environmental and societal impacts, identify and analyse ethical concerns, and adopt an inclusive approach to engineering practice.
Indicative content:
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Identifying, understanding and defining the problem
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Identifying system goals and constraints
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Evaluate and select appropriate Processor system(s) and peripherals.
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Understanding of hardware and software I/O and relevant interfacing technologies
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Developing a solution that meets the system's goals and constraints
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Evaluating the solution
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Evaluate the environmental and societal impact of solutions to complex problems and minimise adverse impacts, while reflecting upon their career aspirations.
This module builds upon concepts and practical approaches introduced at level 4 and will prepare you for sandwich placement and for level 6 project.
Elective modules
This module is for undergraduate students to study abroad in their second year, Semester 2 (only for courses that offer this option). With this module, you can spend a semester at one of the University’s approved partner institutions worldwide – from Europe to the Americas, Australia or Canada.
Study Abroad plays an important role in the University's commitment to an engaging, challenging, and thriving learning culture. It offers opportunities to experience other academic cultures and foster intellectual maturity while enhancing co-curricular skills and students' long-term employability.
Study abroad for credit is permitted on existing university-approved courses only. Students are awarded credits and grades at the partner institution, which are converted into Sheffield Hallam credits and grades on return and included in the Sheffield Hallam degree classification.
Please check and refer to the webpage How study abroad works. You must submit a Learning Agreement outlining the modules you will be taking at the partner institution. The Learning Agreement will be signed off by your academic tutor to ensure that the Learning broadly covers the Learning Outcomes set out in your course curriculum during your study abroad.
Year 4
Optional modules
Module aim:
The aim of this module is to enhance students’ professional development through the completion of and reflection on meaningful work placement(s).
A work placement will provide students with opportunities to experience the realities of professional employment and experience how their course can be applied within their chosen industry setting. The placement will:
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Allow student to apply the skills, theories and behaviours relevant and in addition to their course
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Enable students to enhance their interpersonal skills in demand by graduate employers – communication, problem solving, creativity, resilience, team work etc.
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Grow their student network and relationship building skills.
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Provide student with insights into the industry and sector in which their placement occurs
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Help student make informed graduate careers choices.
Indicative Content:
In this module students undertake a sandwich placement (min 24 weeks / min 21 hours per week) which is integrated, assessed and aligned to their studies.
Their personal Placement Academic Supervisor (PAS) will be their key point of contact during their placement and will encourage and support students to reflect on their experience, learning and contribution to the organisation they work for.
To demonstrate gains in professional development, students will be required to share their progress, learning and achievements with their Placement Academic Supervisor and reflect on these for the summative piece of work.
Final year
Compulsory modules
Module Aim:
This module will develop the skills and knowledge needed that will allow students to identify and analyse tasks that can be automated using real-time input devices (sensors and vision) to control and produce desirable behaviours in robotic devices. This module fuses together software techniques with hardware.
Module Delivery:
This module will be delivered via a mixture of lectures and practical laboratory sessions.
Indicative Content:
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Machine vision, including colour, object and feature detection and identification
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Sensor and actuator applications
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Simulation and modelling techniques
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Embedded robotic devices
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Control algorithms
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Handling real-time data
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Human-machine interactions and interfaces
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Safety and ethics of automated advanced robotics
This module expands your experience of designing and creating gameplay prototypes for Windows-based PCs, using high-level commercial engines such as Unity and Unreal. You’ll build on your existing commercial engine skills to develop a gameplay prototype for a mobile platform.
You’ll study topics such as:
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Game development in a scripting language such as Lua and C#
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Researching and applying common design paradigms to mobile gaming
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Advanced techniques of a commercial games engine
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Particle systems, shader programming, post-processing effects and networking
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Monetisation of the mobile gaming platforms
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Common industry practices to mobile game financing
This module is a research project of your choice – you’ll identify a computer-based problem, investigate the requirements, analyse results of research undertaken and design, and develop and evaluate a solution to that problem. You’ll then evaluate the project’s success, your learnings and opportunities for further work.
You’ll apply skills and learning such as:
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Ideation and planning a larger-scale project
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Information gathering and literature reviews
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The selection of tools, techniques or methods
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Implementation, testing and user evaluation
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Critical reflection on project deliverables, success or failure
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Referencing and citation techniques
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Legal, social, and ethical considerations
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Security and confidentiality
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Sustainable development and deployment
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Employability skills and attributes
Elective modules
This module explores some of the important applications we use – from Google and Amazon to the many social media platforms – which have built their utility and success on top of machine learning systems. Using Python programming and a range of libraries, you’ll learn to understand recognition, prediction, rankings, recommendation systems, social bookmarking and more.
You’ll study topics such as:
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Machine learning in AI, social media, and web applications
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Python libraries for machine learning
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Recommendations based on the ‘likes’ of individuals and groups
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Using neural networks to learn about computer vision tasks
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Ranking search results based on the context they were created in
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Building pricing models using a variety of techniques
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Building systems whose intelligence evolves using genetic algorithms
This module introduces the practice of secure software engineering, exploring the main objectives of security in the construction of large complex applications. We’ll view historical cases of software failure to demonstrate the main problems and implications for poor security practices in software development, which you’ll use as motivation for the study of current software and security engineering practices.
You’ll study topics such as:
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Information security concepts, objectives and properties
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Confidentiality, integrity availability
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Security in the software development lifecycle
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Cryptography foundation and application
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Digital identity management and access control
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Identification, authentication, authorisation and audit
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Vulnerabilities, threats and attacks
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Protection and defence mechanisms and tools
Fees and funding
Home students
Our tuition fee for UK students on full-time undergraduate degree courses in 2025/26 is £9,535 per year (capped at a maximum of 20% of this during your placement year). These fees are regulated by the UK government and therefore subject to change in future years.
If you are studying an undergraduate course, postgraduate pre-registration course or postgraduate research course over more than one academic year then your tuition fees may increase in subsequent years in line with Government regulations or UK Research and Innovation (UKRI) published fees. More information can be found in our terms and conditions under student fees regulations.
International students
Our tuition fee for International/EU students starting full-time study in 2025/26 is £17,155 per year (capped at a maximum of 20% of this during your placement year)

Financial support for home/EU students
How tuition fees work, student loans and other financial support available.
Additional course costs
The links below allow you to view estimated general course additional costs, as well as costs associated with key activities on specific courses. These are estimates and are intended only as an indication of potential additional expenses. Actual costs can vary greatly depending on the choices you make during your course.
General course additional costs
Additional costs for School of Computing and Digital Technologies (PDF, 131.3KB)Legal information
Any offer of a place to study is subject to your acceptance of the University’s Terms and Conditions and Student Regulations.