Computer Science (Artificial Intelligence)
Entry requirements
120-128 UCAS points to include a minimum of 2 A Levels Applicants are required to have Grade B/5 in GCSE Maths. If you hold a Grade C/4 in GCSE Maths, please contact the institution
Considered in combination.
Pass Access to HE Diploma (e.g. Computing/IT/Science/ Humanities/Engineering) with at least 33 Level 3 credits at Merit and/or Distinction to include 12 credits at level 3 in Maths with Merit.
Considered in combination.
Considered in combination
International Baccalaureate Diploma Programme
Maths and English accepted within as GCSE equivalent.
120-128 UCAS points from Higher Level Maths and English considered within as GCSE equivalent at H1-H7 or O1-O4
Considered in combination.
Considered in combination.
Considered in combination. Applicants are required to have Grade B/5 in GCSE Maths We will consider Maths modules within the BTEC alongside Grade C/4 GCSE Maths - enquire at institution.
Considered in combination. Applicants are required to have Grade B/5 in GCSE Maths We will consider Maths modules within the BTEC alongside Grade C/4 GCSE Maths - enquire at institution.
Considered in combination. Applicants are required to have Grade B/5 in GCSE Maths We will consider Maths modules within the BTEC alongside Grade C/4 GCSE Maths - enquire at institution.
Pearson BTEC Level 3 National Extended Diploma (first teaching from September 2016)
Applicants are required to have Grade B/5 in GCSE Maths We will consider Maths modules within the BTEC alongside Grade C/4 GCSE Maths - enquire at institution.
Considered in combination. Applicants are required to have Grade B/5 in GCSE Maths We will consider Maths modules within the BTEC alongside Grade C/4 GCSE Maths - enquire at institution.
Considered in combination.
120-128 UCAS points to include 2 Advanced Highers Applicants are required to have Grade B/5 in GCSE Maths or an equivalent
Considered in combination with Advanced Highers
T Level
Merit to Distinction Overall depending on the Mathematics units studying within the T Level pathways
UCAS Tariff
To include a minimum of 2 A Levels Applicants are required to have Grade B/5 in GCSE Maths. If you hold a Grade C/4 in GCSE Maths, please contact the institution
Considered in combination
About this course
This course has alternative study modes. Contact the university to find out how the information below might vary.
Artificial intelligence (AI) is a rapidly growing field within computer science, and this course will give you the skills you need to excel within it. Topics will range from real-word applications of AI to understanding the theoretical underpinnings of the subject, to creating the innovative AI-driven tools that will drive Industry 4.0. You will also focus on the wider ethical and societal implications of AI.
Taught by a team of internationally recognised AI experts with extensive research and commercial experience that is drawn upon in a research-led teaching experience; and providing students with an exciting opportunity to engage with world-leading research.
- **Be inspired by the creativity that our practical, hands-on course nurtures** Our ‘learning through doing’ ethos means you build the skills to make you desirable to employers. You’ll learn from dedicated teaching staff engaged in internationally significant research, actively creating and developing applications.
- **Collaborate and build** Mirroring the teamwork at the heart of the industry, you’ll work in a team to develop work with a real purpose.
- **Get a head-start in the industry** Benefit from a programme with strong links with industry, (e.g. Apple, Microsoft, IBM, Oracle and Intel) and those links are used to embed relevant real-world problems directly into the programmes.
- **Make use of cutting-edge facilities** Students in engineering, science and the arts have access to a range of specialist equipment and innovative laboratories in our engineering and design facility. You'll also have access to specialist laboratories equipped with various hardware and software configurations.
Modules
Year 1: Core modules:
Stage 1 Computing Placement Preparation (BPIE111)
Software Engineering 1 (COMP1000)
Computer Systems (COMP1001)
Cyber Security & Networks (COMP1002)
Algorithms, Data Structures and Mathematics (COMP1003)
Computing Practice (COMP1004)
Year 2
Core modules
Stage 2 Computing Placement Preparation (BPIE211)
Software Engineering 2 (COMP2000)
Information Management & Retrieval (COMP2001)
Artificial Intelligence (COMP2002)
Computing Group Project (COMP2003)
Embedded Programming and the Internet of Things (COMP2008)
Year 3
Core modules
Computing Related Placement (Generic) (BPIE330)
Final year
Core modules
Computing Project (COMP3000)
Machine Learning (COMP3003)
Human-Robot Interaction (COMP3018)
Optional modules
Parallel Computing (COMP3001)
Alternative Paradigms (COMP3002)
Full-Stack Development (COMP3006)
Big Data Analytics (COMP3008)
The modules shown for this course or programme are those being studied by current students, or expected new modules. Modules are subject to change depending on year of entry and up to date information can be found on our website
Assessment methods
For up to date details, please refer to our website or contact the institution directly.
The Uni
University of Plymouth
School of Engineering, Computing and Mathematics
What students say
We've crunched the numbers to see if overall student satisfaction here is high, medium or low compared to students studying this subject(s) at other universities.
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?
Most popular A-Levels studied (and grade achieved)
Computer science
Teaching and learning
Assessment and feedback
Resources and organisation
Student voice
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.
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.
Computer science
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
This is a newly-classified subject area for this kind of data, so we don’t currently have very much information to display or analyse yet. The subject is linked to important and growing computing industries, and over time we can expect more students to study them — there could be opportunities that open up for graduates in these subjects as the economy develops over the next few years.
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.
£25k
£28k
£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.
Computer science
The graph shows median earnings of graduates who achieved a degree in this subject area one, three and five years after graduating from here.
£25k
£28k
£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 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).
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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