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Anglia Ruskin University

Artificial Intelligence (with Placement Year)

UCAS Code: I401

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

Entry requirements


GCSE/National 4/National 5

3 GCSEs at grade C, or grade 4, or above, including English and Maths.

UCAS Tariff

112

from a minimum of 2 A Levels (or equivalent) including A level Mathematics (or equivalent).

About this course


Course option

4.0years

Sandwich | 2021

Subject

Artificial intelligence

Ready to meet the future head-on? From self-driving cars to chess-playing computers, artificial intelligence is shaping our world. Explore the science of machine learning with our Cambridge-based course and be at the forefront of technological innovation. Designed to fill a skills gap and meet a growing need for talented graduates, our AI degree is supported by the Intel AI Academy and offers a placement year, drawing on links with Cambridge high tech hub companies such as Cambridge Spark and Amazon.

Artificial Intelligence, the computer emulation of human thinking, has been identified by the UK Government as the first of its four Grand Challenges to keep the UK at the forefront of technological innovation and industrial development.

AI is an ever-evolving subject area that requires you to remain aware of constant changes and developments, as well as current issues that AI faces.

Our brand new degree course has been designed with employers and industry in mind, ensuring you are learning the professional skills you will need once you graduate. You will be provided with the knowledge and skills to develop as a specialist in the areas of data analysis, machine learning, neural networks and artificial intelligence algorithm design. You'll also have access to Intel’s AI Academy, an online data processing resource. You will learn the history of Artificial Intelligence, systems needed to underpin AI and the advanced algorithms it employs, using up-to-date technology including software packages and hardware infrastructure.

Through this course you will gain the knowledge needed to display good professional judgement and responsibility in addressing commercial, environmental and ethical factors found in the various areas where AI is used.

If you enjoy mathematics and want to apply these fundamentals in a practical way – combining them with programming, computer systems and software design to create practical solutions to everyday technological issues – Artificial Intelligence is the subject for you.

Modules

Level 4 modules
Introduction to Programming
Computer Systems
Computer Modelling and Simulation
Fundamentals of AI
Introduction to Mathematical Techniques for Artificial Intelligence
Level 5 modules
Advanced Analytical Techniques for AI
Database Design and Implementation
Software Engineering
Digital Security
Machine Learning
Artificial Neural Networks
Level 5 optional modules
Object Oriented C++
Microprocessor Systems Design
Work placement

Level 6 modules
Final Project
AI Techniques (Fuzzy Logic and Genetic Algorithms)
Professional Issues: Computing and Society
Deep Learning
Distributed-Systems Programming
Level 6 optional modules
Image Processing
Digital Signal Processing
Internet Services, Data Analytics and the Cloud
Ethical Hacking and Countermeasures

Tuition fees

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

Channel Islands
£9,250
per year
England
£9,250
per year
EU
£9,250
per year
Northern Ireland
£9,250
per year
Scotland
£9,250
per year
Wales
£9,250
per year

The Uni


Course location:

Cambridge Campus

Department:

Computing and Technology

TEF rating:
Read full university profile

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.

Computer science

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?

73%
UK students
27%
International students
84%
Male students
16%
Female students
63%
2:1 or above
11%
Drop out rate

Most popular A-Levels studied (and grade achieved)

C
D
E

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.

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.

£21,500
med
Average annual salary
85%
low
Employed or in further education
68%
low
Employed in a role where degree was essential or beneficial

Top job areas of graduates

47%
Information technology and telecommunications professionals
9%
Information technology technicians
8%
Sales assistants and retail cashiers

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.

What about your long term prospects?

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

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.

£21k

£21k

£25k

£25k

£28k

£28k

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 is the percentage of applicants to this course who received an offer last year, through Ucas.

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This is what the university has told Ucas about the course. Use it to get a quick idea about what makes it unique compared to similar courses, elsewhere.

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Course location and department:

This is what the university has told Ucas about the course. Use it to get a quick idea about what makes it unique compared to similar courses, elsewhere.

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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?

Have a question about this info? Learn more here