BSc (Hons) Artificial Intelligence

• 104 UCAS points. We accept a full range of qualifications that carry UCAS points, including A-levels, BTECs and T-levels. Please see our guide to the UCAS Tariff for examples of how to achieve these points. For most courses, we are also able to consider non-tariffable qualifications.
• Any subjects are acceptable at Level 3. Relevant science, technology, engineering or mathematics (STEM) and computing-related subjects are preferred.
• You should also have five GCSEs at grade C or above or grade 4 to 9 (or equivalent), including English and Mathematics.
• We'll be happy to consider your application if you don't meet the standard entry requirements but have non-traditional qualifications and/or relevant experience. You'll be required to undertake an assessment to determine your suitability for the course. You'll be assessed on your problem-solving skills and ability to participate in group work.
• You may be required to attend an interview and/or provide a portfolio of work.
• If English isn’t your first language, you’ll also need IELTS 6.0 with no less than 5.5 in any band (or equivalent). We also accept a range of other English language qualifications – please visit our English Language Requirements web page for more details.

Where changes are made to material information contained in this course description or a decision is taken to suspend a course between the offer of admissions and enrolment, we will inform applicants at the earliest possible opportunity and will outline the various options available to the applicant.

Bolton University's BSc (Hons) in Artificial Intelligence is ideal if you wish to pursue a career at the cutting edge of AI, helping to turn technological innovations into meaningful solutions that transform the way we live. It offers you the opportunity to develop a deep understanding of the scientific and practical applications of programming and computation in the fast-moving field of AI and machine learning.

As a graduate of this degree, you'll possess a solid understanding of the core technologies underpinning AI and be able to demonstrate your skills in applying AI concepts and methodologies to solve problems. You'll have strong programming skills in several programming languages and valuable knowledge in essential areas such as machine learning, deep learning and natural language processing.

You'll also be able to demonstrate vital transferable skills, including teamwork, leadership, communication, time management, commercial awareness, problem-solving and negotiation.

What can I do with this qualification?

Alternative career options

Graduates can also use the qualification as a stepping-stone into a range of other careers. Some of these roles may require relevant experience and/or postgraduate study. Possible fields include:

• Teaching
• Research and development
• Social media management
• Technical writing
• Product management
• ICT Training
• ICT sales
• Digital copywriting
• Telecommunications
• Network engineering
• Cyber analyst
• Machine security professional

Home/EU Fees

Home students starting this course in the first year will be required to pay a Home fee of £6,000 for the academic year 2024/25.

International Fees

No fee information is currently available, please contact the University of Bolton’s Academic Fees team by emailing AcademicFees@bolton.ac.uk for more information.

Bursaries

Click here for more information about the scholarships and bursaries available to University of Bolton students.

Important note regarding tuition fees for the 2024-25 academic year: EU nationals who meet residency requirements (have settled or pre-settled status) may be eligible for 'Home' fee status. If you do not meet these residency requirements, overseas fees will apply. Irish citizens living in the UK or Ireland will be eligible for 'Home' fee status under the Common Travel Area arrangement. Please read the student finance for EU students web page on www.gov.uk for information.

The fees for a student's course of study will be set for the normal duration of that course subject only to inflationary increases – measured by the Consumer Price Index (CPI) recorded in March each year to take effect for subsequent start dates.

We understand that our students' learning needs and preferred learning styles vary, so we use a range of learning and teaching methods, including online (where appropriate). Our team of highly knowledgeable and enthusiastic lecturers offer face-to-face sessions and one-to-one support. We'll also assign you a dedicated personal tutor to help guide you through your studies.

Lectures introduce the core course content, while practical laboratory sessions offer practical experience and help consolidate your learning. Tutorials allow you to ask questions to ensure you understand the topics covered in lectures and laboratory sessions. We use case studies and practical scenarios to help you learn to apply academic theory to real-life problems, allowing you to gain insights into AI in commercial environments.

Guest lectures/presentations by a variety of visiting speakers from relevant employment areas offer you the chance to develop your knowledge and understanding further.

Regarding assessment, you can expect time-constrained exams and coursework, such as essays, reports, presentations, portfolios, and others. These contribute to your final marks and allow you to demonstrate that you've met the learning outcomes for the course.

We also use other forms of assessment to help you learn, provide you with feedback and inform your development, though these do not count towards your final marks. For instance, you might be asked to complete quizzes or undertake practical exercises. You'll also receive feedback on assessment drafts. These will help identify any areas that would benefit from extra attention on your part or where you need additional support from your tutor.

We take our social, public and ethical responsibilities very seriously. All our student project work conforms with the University's policies on ethics and uses the University's research ethics procedure before work commences.

Modules

The modules listed below may be a mixture of compulsory and optional. You may not have the opportunity to study all the modules shown as part of the course.

• Maths for Computing
• Computer Science Fundamentals
• Computing Infrastructure
• Databases
• Object Oriented Programming
• Introduction to AI
• Computer Vision and Image Processing
• Data Structures and Algorithms
• Advanced Databases and Big Data
• Research and Professional Issues
• Undergraduate Project
• Natural Language Processing
• Computer Graphics
• Applied Machine Learning
• Emerging Technologies

Assessment methods

Learning Activities

The university will use all reasonable endeavours to deliver your course as described in its published material and the programme specification for the academic year in which you begin your course. The university considers changes to courses very carefully and the university will minimise any changes. Please be aware that our courses are subject to review on an ongoing basis and changes may be necessary due to legitimate staffing, financial, regulatory and academic reasons. The content of course modules and mode of associated assessments may be updated on an annual basis. This is to ensure that all modules are up-to-date and responsive to employment and sector needs. The published course material and the programme specification contain indicative ‘optional modules’ that may be subject to change due to circumstances outside of our control. For this reason, we cannot guarantee to run any specific optional module.