The Artificial Intelligence with Computer Science degree will enable you to provide solutions to real-world problems that require the acquisition and representation of information, knowledge and intelligence within computerised processes, which form the basis for intelligent computer systems powered by Artificial Intelligence.
Entrants develop skillsets particular to pattern identification, the modelling of processes or actions associated with those patterns and the utilisation of machine learning techniques that automate this process alongside mainstream computing topics that form a foundation for working with AI.
The development of the Artificial Intelligence with Computer Science degree is rooted in the knowledge and experience of Computer Science and Artificial Intelligence (CSAIP) research unit members, their experiences with collaborative projects spanning over twenty years and feedback from past and present students relating to their educational experience and preferences associated with delivery of Artificial Intelligence.
The wellbeing and health and safety of our students and staff is paramount to us. We are committed to delivering all of our courses and services as safely as possible. Due to the pandemic, the methods and activities adopted for the coming year may differ from those previously published and may be subject to further change through the course of your study if such change is necessary due to public health concerns, health and safety guidance or in response to Government Guidelines. USW is committed to providing you with a fantastic student experience and a wealth of support, and you can hear how students have benefitted from this approach here: Learn more about blended learning.
The Artificial Intelligence with Computer Science degree is structured around six main themes, or pillars, that are developed through year of study, specifically:
Mainstream programming tailored to producing software solutions that encompass artificial intelligence and their foundations:
Logic programming and machine learning approaches rooted in the understanding and application of methods, tools and packages appropriate to a general audience:
Information system and database development that ultimately leads to the application of Data Science techniques for the mining of information:
Computer System Concepts that address hardware, software, operating systems and networking:
Project work that allow for the development of management, planning, development and review of solutions developed in teams and individually:
Mathematical foundations for computational intelligence and computer science:
Subject to Validation
This undergraduate computing course is delivered in a traditional format.
Full-time students will typically spend 12 hours in classes and 24 hours outside of classes each week.
If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects.
You will need to spend a significant amount of time working independently, reading and preparing for assessments.
Assessment is primarily by coursework, varying from a research-style paper or essay to practical assignments. You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.
Assessment is primarily by coursework, varying from a research-style paper or essay to practical assignments to presentations and team based project work.
You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.
Practice is so important in gaining understanding of applied techniques, which is why we have a range of high specification computer laboratories including workrooms dedicated to our masters’ students.
These facilitate a learning environment where you can work individually or in groups and as they are located close to the staff offices.
Information about your main teaching team and their research interests can be found on the Computer Science and Artificial Intelligence Paradigms (CSAIP) website.
GCSEs: The University normally requires a minimum 5 GCSEs including Mathematics/Numeracy and English at Grade C or Grade 4 or above, or their equivalent, but consideration is given to individual circumstances.
BCC - CDD (this is equivalent to 104-80 UCAS tariff points).
Pass the Advanced Welsh Baccalaureate Diploma with Grade C/D in the Skills Challenge Certificate and BC - CD at A Level (this is equivalent to 104-80 UCAS tariff points).
BTEC Extended Diploma Distinction Merit Merit - Merit Merit Pass (this is equivalent to 112-80 UCAS tariff points).
Pass the International Baccalaureate Diploma with a minimum score of 29 overall including 5 or above in English at standard level
Pass the Access to HE Diploma and obtain a minimum of 80 UCAS tariff points
Full-time fees are per year. Part-time fees are per 20 credits. Once enrolled, the fee will remain at the same rate throughout the duration of your study on this course.
Students have access to a wide range of resources including textbooks, publications, and computers in the University’s library and via online resources. In most cases they are more than sufficient to complete a course of study. Where there are additional costs, either obligatory or optional, these are detailed below. Of course students may choose to purchase their own additional personal resources/tools over and above those listed to support their studies at their own expense. All stationery and printing costs are at a student’s own expense.
UK and EU students
Apply via UCAS if you are a UK/EU residing applicant, applying for year one of a full-time undergraduate degree, Foundation Year, Foundation Degree or HND and you have not applied through UCAS before. If you are applying to study part-time, to top up your Foundation Degree or HND, or to transfer to USW from another institution, please apply directly.
Apply directly to the University if you live outside the UK/EU.
Erasmus opportunities for attendance at summer schools in Advanced Computer Vision and Machine Learning.
Partners: TEI of Crete, University of Patras, University of Burgundy, Cyprus University of Technology, University of South Wales, Polytechnic Institute of Porto, University of Salento.
Possible career options include: Artificial Intelligence, Competitive Intelligence, Business Intelligence, Threat Intelligence, Cyber Intelligence, Computational Intelligence, Customer Intelligence and Marketing Intelligence account for 8% of vacancies according to Jobswatch IT UK over the past six months. These roles require particular skillsets and their share of the market has increased. Example job titles include Machine Learning Engineer, Artificial Intelligence Engineer and Business Intelligence Data Engineer.