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University of South Wales

Artificial Intelligence with Computer Science

UCAS Code: G800

Bachelor of Science (with Honours) - BSc (Hons)

Entry requirements


A level

C,D,D-B,C,C

Pass the Access to HE Diploma and obtain a minimum of 80 UCAS tariff points

GCSE/National 4/National 5

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.

Pass the International Baccalaureate Diploma with a minimum score of 29 overall including 5 or above in English at standard level

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

DMM-MMP

UCAS Tariff

104-80

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).

About this course


Course option

3.0years

Full-time | 2021

Subject

Artificial intelligence

This course develops graduates with a capacity for providing 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 (AI).

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 course 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 AI.

Modules

Mainstream programming tailored to producing software solutions that encompass artificial intelligence and their foundations.

Year 1: Introduction to Programming

Year 2: Agent Based Systems

Year 3: Robotics and Autonomous Systems

Logic programming and machine learning approaches rooted in the understanding and application of methods, tools and packages appropriate to a general audience.

Year 1: Logic Programming and Knowledge Representation

Year 2: Intelligent Decision Support Systems

Year 3: Machine Learning and Natural Intelligence

Information system and database development that ultimately leads to the application of Data Science techniques for the mining of information.

Year 1: Information Management, Assurance and Security

Year 2: Database Development

Year 3: Data Mining

Computer System Concepts that address hardware, software, operating systems and networking.

Year 1: Computer System Concepts

Year 2: Operating System Concepts

Year 3: Computer Networks

Project work that allow for the development of management, planning, development and review of solutions developed in teams and individually.

Year 1: Immersive Learning Team Project

Year 2: Professional Practice and Employability Team Project

Year 3: Individual Project

Mathematical foundations for computational intelligence and computer science.

Year 1: Mathematical Tools for Computation

Year 2: Computational Mathematics

Assessment methods

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.

Tuition fees

Select where you currently live to see what you'll pay:

England
£9,000
per year
EU
£9,000
per year
International
£12,600
per year
Northern Ireland
£9,000
per year
Scotland
£9,000
per year
Wales
£9,000
per year

The Uni


Course location:

Pontypridd

Department:

Computing and Mathematics

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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.

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?

88%
UK students
12%
International students
89%
Male students
11%
Female students
66%
2:1 or above
20%
Drop out rate

Most popular A-Levels studied (and grade achieved)

C
B
C

After graduation


We don't have more detailed stats to show you in relation to this subject area at this university but read about typical employment outcomes and prospects for graduates of this subject below.

What about your long term prospects?

Looking further ahead, below is a rough guide for what graduates went on to earn.

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.

£20k

£20k

£25k

£25k

£25k

£25k

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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Course location and department:

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Teaching Excellence Framework (TEF):

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This information comes from the National Student Survey, an annual student survey of final-year students. You can use this to see how satisfied students studying this subject area at this university, are (not the individual course).

We calculate a mean rating of all responses to indicate whether this is high, medium or low compared to the same subject area at other universities.

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This information is from the Higher Education Statistics Agency (HESA).

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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