Robotic Engineering & Artificial Intelligence with Professional Placement
Kingston University
UCAS Code: H901 | Bachelor of Engineering (with Honours) - BEng (Hon)
Kingston University
UCAS Code: H901 | Bachelor of Engineering (with Honours) - BEng (Hon)
Entry requirements
A level
A-levels to include Mathematics and a Science subject (Physics, Chemistry, Computer Science, Computing, Design and Technology or Electronics).
Access to HE Diploma
Equivalent of 128 UCAS points in a relevant Engineering subject which has been passed with all Maths and Physics units at Level 3.
International Baccalaureate Diploma Programme
Must include Grade 5 in Maths & one Science subject at Higher Level.
Leaving Certificate - Higher Level (Ireland) (first awarded in 2017)
Equivalent to 128 UCAS points with a minimum of H2 from Maths and one Science subject.
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
Engineering or related subject such as Aerospace / Aeronautical / Electrical / Electronic / Manufacturing and Mechanical Engineering will be considered.
Equivalent of 128 UCAS points which must include Maths and one Science subject in Advanced Highers.
T Level
UCAS Tariff
UCAS points from 3 A-Levels or equivalent Level 3 qualifications.
About this course
**Reasons to choose Kingston University**
- Focus on the core principles of robotic engineering and applied artificial intelligence. This programme is designed to provide you with the skills and knowledge highly valued in the rapidly evolving industrial, commercial, and domestic sectors.
- Solve real-world robotics challenges using artificial intelligence.
- Explore robotics, autonomous systems, artificial intelligence, machine learning, computer vision, and intelligent control systems.
- Work alongside peers from various cultural, social, and professional backgrounds on team-based projects. This collaboration encourages appreciation for diversity, enhances your ability to understand different perspectives, and cultivates an inclusive mindset, which is essential for future engineering professionals.
**About this course**
Robotic Engineering and Artificial Intelligence stand at the cutting edge of technological progress to address some of the most pressing challenges facing society today, encompassing innovations such as industrial robotic arms, autonomous vehicles, aerial drones and space robots. As a student on this course, you will acquire the vital skills and knowledge required to tackle these intricate challenges, opening up a world of possibilities at the intersection of these two potent fields, and ultimately making a significant impact on a global level.
Our hand-on course equips you with the Future Skills needed to thrive in the rapidly evolving technological landscape. Discover how to harness the power of artificial intelligence and other state-of-the-art technologies to design and develop intelligent systems and contribute to the development of innovative solutions that can make a positive impact on society. The course will prepare you for a career in a wide range of fields and ensure that you are well-positioned to take advantage of the opportunities presented by the Fourth Industrial Revolution.
Embrace the UN Sustainable Development Goals as a guiding force for a sustainable future for all. In this course, you will learn how to integrate these goals into your professional endeavours, actively contributing to their achievement. Our diverse and inclusive curriculum, crafted to meet the needs of varied communities, is delivered by academics from diverse backgrounds. This unique learning experience allows students to engage with people from different cultures and perspectives, enriching their understanding and broadening their horizons.
**Future Skills**
Embedded within every course curriculum and throughout the whole Kingston experience, Future Skills will play a role in shaping you to become a future-proof graduate, providing you with the skills most valued by employers such as problem-solving, digital competency, and adaptability.
As you progress through your degree, you'll learn to navigate, explore and apply these graduate skills, learning to demonstrate and articulate to employers how future skills give you the edge.
At Kingston University, we're not just keeping up with change, we're creating it.
Modules
Example modules: – Introduction to Robotics - Machine Learning and Computer Vision - Modelling and Simulation in Soft Robots - For a full list of modules please visit the Kingston university course webpage
Assessment methods
Teaching includes lectures, seminars, tutorials and practical laboratory sessions, backed up by design classes, workshops and site visits.
Assessment methods are usually split between exam and continuous assessment coursework (e.g. reports, computer exercises, laboratories and essays). Some modules are assessed by coursework only.
Tuition fees
Select where you currently live to see what you'll pay:
The Uni
Kingston University
Department of Mechanical Engineering
What students say
How do students rate their degree experience?
The stats below relate to the general subject area/s at this university, not this specific course. We show this where there isn’t enough data about the course, or where this is the most detailed info available to us.
Production and manufacturing engineering
Sorry, no information to show
This is usually because there were too few respondents in the data we receive to be able to provide results about the subject at this university.
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
Artificial intelligence
Sorry, no information to show
This is usually because there were too few respondents in the data we receive to be able to provide results about the subject at this university.
Who studies this subject and how do they get on?
Most popular A-Levels studied (and grade achieved)
After graduation
The stats in this section relate to the general subject area/s at this university – not this specific course. We show this where there isn't enough data about the course, or where this is the most detailed info available to us.
Production and manufacturing engineering
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Graduates are in significant demand, so unemployment rates are well below the national graduate average and starting salaries are well above average. Much the most common industries for these graduates are now vehicle manufacture - there are not enough people with these degrees to go round and so the big employers tend to take the lion's share at the moment. But pretty much anywhere there is manufacturing, there are production engineers. Bear in mind that a lot of courses are four years long, and lead to an MEng qualification — this is necessary if you want to become a Chartered Engineer.
Artificial intelligence
What are graduates doing after six months?
This is what graduates told us they were doing (and earning), shortly after completing their course. We've crunched the numbers to show you if these immediate prospects are high, medium or low, compared to those studying this subject/s at other universities.
Top job areas of graduates
Artificial intelligence is a very specialist subject taken by less than 100 people a year at the moment, so there is little reliable information available on graduate prospects - bear that in mind when you review the stats above. Graduates taking this type of subject are more likely than other computing graduates to go into further research. However, if you want to find out more specifically about the potential graduate outcomes of a specific course, it's a good idea to go on open days and talk to tutors about what previous graduates have gone on to do.
What about your long term prospects?
Looking further ahead, below is a rough guide for what graduates went on to earn.
Production and manufacturing engineering
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£22k
£30k
£35k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
Artificial intelligence
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£23k
£30k
£34k
Note: this data only looks at employees (and not those who are self-employed or also studying) and covers a broad sample of graduates and the various paths they've taken, which might not always be a direct result of their degree.
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This is the percentage of final-year students at this university who were "definitely" or "mostly" satisfied with their course. We've analysed this figure against other universities so you can see whether this is high, medium or low.
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This information is from the Higher Education Statistics Agency (HESA), for undergraduate students only.
You can use this to get an idea of who you might share a lecture with and how they progressed in this subject, here. It's also worth comparing typical A-level subjects and grades students achieved with the current course entry requirements; similarities or differences here could indicate how flexible (or not) a university might be.
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Post-six month graduation stats:
This is from the Destinations of Leavers from Higher Education Survey, based on responses from graduates who studied the same subject area here.
It offers a snapshot of what grads went on to do six months later, what they were earning on average, and whether they felt their degree helped them obtain a 'graduate role'. We calculate a mean rating to indicate if this is high, medium or low compared to other universities.
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Graduate field commentary:
The Higher Education Careers Services Unit have provided some further context for all graduates in this subject area, including details that numbers alone might not show
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The Longitudinal Educational Outcomes dataset combines HRMC earnings data with student records from the Higher Education Statistics Agency.
While there are lots of factors at play when it comes to your future earnings, use this as a rough timeline of what graduates in this subject area were earning on average one, three and five years later. Can you see a steady increase in salary, or did grads need some experience under their belt before seeing a nice bump up in their pay packet?
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