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Liverpool Hope University

Artificial Intelligence (with Year in Industry)

UCAS Code: GH79

Master in Science (with Honours) – MSci (Hon)

Entry requirements


A level

B,B,C

Credits gained must equate to at least 112 Tariff Points

This qualification can only be accepted in conjunction with other relevant qualifications

International Baccalaureate Diploma Programme

26

112 Tariff Points from Higher Level qualifications only

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

DMM

Qualifications must equate to at least 112 Tariff Points

UCAS Tariff

112

UCAS Tariff points must come from a minimum of two A Levels (or equivalent). Additional points can be made up from a range of alternative qualifications.

This qualification can only be accepted in conjunction with other relevant qualifications

About this course


Course option

5.0years

Full-time with year in industry | 2021

Subject

Artificial intelligence

We are **on the brink of a technological revolution** that will profoundly alter the way we live, work, and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before. Artificial Intelligence (AI) systems are being developed today that would have been considered to belong to the realms of science fiction only a couple of years ago. The pace of change in AI is such that it has blindsided many politicians and policymakers. A very few are only now, at this late stage, becoming aware of the **potentially massive disruptive impact of AI** on all aspects of life in the 21st century. What is in no doubt is that the direction that AI takes will have a profound impact on all of our futures.

There is a major skills shortage of AI practitioners developing. A critical perquisite for this to be addressed is to understand how AI works; what it can and can’t yet do, what it may be capable of, how to utilise it, and how to develop AI in a responsible, scientific and ethical way. This course will teach you about the practical aspects of AI: how it works, what it can do, how it can be practically utilised for many different purposes, how it may develop in the future, and how to be part of the AI based industries of the future. **You will spend your third year on compulsory placement in industry.**

Modules

Liverpool Hope University offers an integrated curriculum. Please go to the course link provided for further information on the topics you will study as part of this degree.

Assessment methods

Students are assessed via a number of methods. Please go to the course link provided for further information.

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
International
£11,400
per year
Northern Ireland
£9,250
per year
Scotland
£9,250
per year
Wales
£9,250
per year

The Uni


Course location:

Hope Park

Department:

Department of Mathematics and Computer Science

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.

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?

95%
UK students
5%
International students
82%
Male students
18%
Female students
87%
2:1 or above
18%
Drop out rate

Most popular A-Levels studied (and grade achieved)

B
D
C

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.

£20,000
low
Average annual salary
100%
high
Employed or in further education
81%
med
Employed in a role where degree was essential or beneficial

Top job areas of graduates

40%
Information technology and telecommunications professionals
16%
Teaching and educational professionals
10%
Sales, marketing and related associate professionals

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.

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.

£18k

£18k

£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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This is what the university has told Ucas about the criteria they expect applicants to satisfy; some may be compulsory, others may be preferable.

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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):

We've received this information from the Department for Education, via Ucas. This is how the university as a whole has been rated for its quality of teaching: gold silver or bronze. Note, not all universities have taken part in the 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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