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Robotic Engineering & Artificial Intelligence

Study level:
Undergraduate

Course summary

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 method

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.

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How to apply

Apply by
29 January

This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.

Application codes

Course code:
H900
Institution code:
K84
Campus name:
Main Site
Campus Code:
-

Points of entry

The following entry points are available for this course:

  • Year 1

Open days

Entry requirements

Qualification requirements

UCAS Tariff - 128 - 144 points

UCAS points from 3 A-Levels or equivalent Level 3 qualifications.

A level - ABB - AAA

A-levels to include Mathematics and a Science subject (Physics, Chemistry, Computer Science, Computing, Design and Technology or Electronics).

Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016) - DDM - DDD

Engineering or related subject such as Aerospace / Aeronautical / Electrical / Electronic / Manufacturing and Mechanical Engineering will be considered.

Access to HE Diploma - D: 30 credits M: 15 credits

Equivalent of 128 UCAS points in a relevant Engineering subject which has been passed with all Maths and Physics units at Level 3.

Scottish Higher

Equivalent of 128 UCAS points to include Maths and one Science subject in Advanced Highers.

International Baccalaureate Diploma Programme - 28 points

Must include grade 5 in Maths and one Science subject at Higher Level.

Leaving Certificate - Higher Level (Ireland) (first awarded in 2017) - H2, H2, H2, H3, H3

Equivalent to 128 UCAS points with a minimum of H2 from Maths and one Science subject.

T Level - D

Find out more about qualification requirements for this course.

Contextual admissions

Universities and colleges consider more than grades when assessing applications and may make offers based on a range of criteria. Learn more about contextual offers.

When assessing your application, we’re looking for evidence of your ability, potential, passion for your subject and the skills and experience you have to evaluate your suitability for a course.

Our course entry requirements include tariff ranges. We vary the required UCAS Tariff points in our offers as we consider each application individually and use a number of factors to build an offer that is tailored to you, this includes your personal statement and predicted grades.

Learn more on the Kingston University website

Historical entry grades data

This section shows the range of grades students were previously accepted with - learn more. It is designed to support your research but does not guarantee whether you will or won't get a place. Admissions teams consider various factors, including interviews, subject requirements, and entrance tests. Check all course entry requirements for eligibility.

Not enough data available

We are unable to show previous accepted grades for this course. This could be because the course is new, it's a postgraduate course, there isn't enough historical data, or the provider has opted out of sharing their entry grades data for this course - learn more.

Student Outcomes

Operated by the Office for Students

The number of student respondents and response rates can be important in interpreting the data – it is important to note your experience may be different from theirs. This data will be based on the subject area rather than the specific course. Read more about this data on the Discover Uni website.

Fees and funding

Tuition fees

No fee information has been provided for this course

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website.

Additional fee information

For international fees, please visit:
https://www.kingston.ac.uk/undergraduate/fees-and-funding/fees/

Please visit the provider course webpage for further information regarding additional course costs

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