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Artificial Intelligence and Data Science

Entry requirements


A level

B,B,B-B,B,C

Access to HE Diploma

D:15,M:24,P:6

Pass Access to HE Diploma with 60 credits with 45 at Level 3

GCSE/National 4/National 5

GCSE Maths and English Grade 4/Grade C (or above) or equivalent qualification

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

DDM-DMM

T Level

M

UCAS Tariff

112-120

We encourage you to outline all your qualifications and achievements in your application to provide us a full picture. Your offer will typically be based on your predicted and/or achieved grades from full level 3 qualifications or above e.g. A levels, BTEC Ext Diploma, Access to HE, etc. Any subject specifics are outlined below in the A-levels section, and these specifics are applicable across all equivalent qualifications. A strong application/performance and appropriate experience will be taken into account where typical criteria is not met.

About this course


Course option

3years

Full-time | 2024

Subject

Artificial intelligence

**Course information**

Dealing with data is one of the biggest challenges that society faces – but it also offers huge opportunities. From autonomous vehicles to medical systems, data science and AI is penetrating nearly every industry. And with the demand for AI skills and data science continuing to grow, now is perfect time to study this area and set yourself up for a successful career. 

**KEY FEATURES OF THE COURSE:**

**EMPLOYABILITY:** Be a graduate that’s sought after by an industry offering attractive salaries and significant progression right from the start of your career
**WORKING WITH INDUSTRY:** Take advantage of our connections with employers on work placements and projects
**NO EXAMS!:** We’ll assess you via other methods throughout your degree instead
**OPTIONAL PLACEMENT YEAR:** Gain valuable experience in industry by taking an optional placement year between years two and three
**FLEXIBILITY:** Benefit from the option to transfer to another degree in our Computing portfolio after your first year

**HOW YOU’LL LEARN**

You’ll learn in a variety of ways – lectures, seminars and tutorials will give you the opportunity to develop understanding. Practical sessions will give you the chance to develop your skills in both equipment use and the evaluation of experimental procedures and data. In your third year you’ll take an Individual Project module where you’ll be encouraged to use and apply research and innovation tools and approached in a practical context. Team working will also allow you to develop interpersonal and communication skills – an important skill for the workplace. 

**YOUR CAREER**

Data Science jobs are becoming increasingly in demand across all sectors including engineering, technology, society, commerce and healthcare. You could move into roles such as: 

- Data scientist 

- Data analyst 

- Data engineer 

- Data architect 

- Machine learning engineer 

- Business intelligence engineer 

**STUDY OPTIONS**
This course is also available with a Foundation Year option.

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
£14,900
per year
International
£14,900
per year
Northern Ireland
£9,250
per year
Scotland
£9,250
per year
Wales
£9,250
per year

The Uni


Course location:

University of Derby

Department:

Department of Computing and Mathematics

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?

80%
UK students
20%
International students
75%
Male students
25%
Female students
67%
2:1 or above
21%
First year drop out rate

Most popular A-Levels studied (and grade achieved)

C
C
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.

£21,500
med
Average annual salary
94%
med
Employed or in further education

Top job areas of graduates

48%
Information technology and telecommunications professionals
14%
Design occupations
12%
Information technology technicians

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.

£23k

£23k

£25k

£25k

£31k

£31k

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 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:

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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).

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?

Have a question about this info? Learn more here