BSc (Honours) Artificial Intelligence and Robotics

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BSc (Honours)

Artificial Intelligence and Robotics

Full-time Computing

Develop the skills and knowledge to create robots that are increasingly intelligent – combining artificial intelligence with principles of electrical engineering to create innovative, autonomous devices.

Everything you need to know...

  • Pound sign

    What is the fee?

    Home: £9,250 per year (£1,200 for placement year)
    International/EU: £16,655 per year (£1,200 for Placement year)

  • Time

    How long will I study?

    3 / 4 Years

  • Location

    Where will I study?

    City Campus

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    What are the entry requirements?

    112-120 UCAS points

  • Checkmark

    What is the UCAS code?

    AA16

  • Date

    When do I start?

    September 2024

  • Avatar

    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.

 


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How you learn

All our courses are designed around a set of key principles based on engaging you with the world, collaborating with others, challenging you to think in new ways, and providing you with a supportive environment in which you can thrive.  

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 our unique student support triangle 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
Michael Meredith
Principal Lecturer in Software Engineering, Graphics and Multimedia

Michael 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

Applied learning

Work placements  

You’ll have the opportunity to complete a year-long work placement between your second and third 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.

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Location

Howard Street
Sheffield
S1 1WB

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Equipment 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

Entry requirements

All students

UCAS points

  • 112-120

This must include at least 64 points from two A levels or equivalent BTEC National qualifications. For example:

  • BBC-BBB at A Level, including a C or above in A-Level mathematics.
  • DDM in BTEC Extended Diploma.
  • Merit overall from a T level qualification
  • A combination of qualifications which may include AS levels, 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

*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.

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.

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

Module and assessment information for future years is displayed as currently validated and may be liable to change. When selecting electives, your choices will be subject to the core requirements of the course. As a result, selections may be limited to a choice between one of two or more specified electives in some instances.

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

Module
Credits
Assessment
Fundamentals Of Analogue & Digital Electronics
Credits 40
Assessment Coursework(50%) , Exam(50%)
Maths And Computational Methods
Credits 40
Assessment Coursework(100%)
Professional Engineering Practice
Credits 20
Assessment Coursework(100%)
Programming For Computer Science
Credits 20
Assessment Coursework(100%)
Year 2

Compulsory modules

Module
Credits
Assessment
Advanced Programming
Credits 20
Assessment Coursework(100%)
Algorithms And Data Structures
Credits 40
Assessment Coursework(100%)
Artificial Intelligence And Machine Learning 1
Credits 20
Assessment Coursework(100%)
Industrial Group Embedded System Project
Credits 40
Assessment Coursework(70%) , Practical(30%)
Year 3

Optional modules

Module
Credits
Assessment
Placement Year
Credits -
Assessment
Final year

Compulsory modules

Module
Credits
Assessment
Advanced Robotics, Automation, Machine Vision, And Sensor Fusion
Credits 40
Assessment Coursework(100%)
Artificial Intelligence And Machine Learning 2
Credits 20
Assessment Coursework(100%)
Development Project
Credits 40
Assessment Coursework(40%) , Practical(60%)

Elective modules

Module
Credits
Assessment
Machine Learning Algorithms And Heuristics
Credits 20
Assessment Coursework(100%)
Secure Software Engineering
Credits 20
Assessment Coursework(100%)

Fees and funding

Home students

Our tuition fee for UK students starting full-time undergraduate study in 2024/25 is £9,250 per year. These fees are regulated by the UK government and are therefore subject to changes in government policy. During your placement year you will pay a reduced fee of £1,200.

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 2024/25 is £16,655 per year. During your placement year you will pay a reduced fee of £1,200.

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Financial support for home/EU students

How tuition fees work, student loans and other financial support available.

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Additional course costs

This link allows you to view estimated costs associated with the main activities on specific courses. These are estimates and, as such, are only an indication of additional course costs. Actual costs can vary greatly depending on the choices you make during your course.

Additional costs for Computing courses (PDF, 197.9KB)

Legal information

Any offer of a place to study is subject to your acceptance of the University’s Terms and Conditions and Student Regulations.

 

How do I apply?

Apply now via UCAS

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Teaching

We are Gold rated in the Teaching Excellence Framework (TEF) for the outstanding quality of our teaching and student outcomes

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Employment

95% of our UK graduates are in work or further study 15 months after graduating (2020/21 Graduate Outcomes Survey)

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