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Heriot-Watt University

Data Sciences

UCAS Code: G3DS

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

Entry requirements


A level

A,B,B

including Mathematics for entry to Year 1. For entry to Year 2: ABB including Mathematics and Computing.

International Baccalaureate Diploma Programme

26

with Mathematics at Higher Level 5 for entry to Year 1. For entry to Year 2: A total of 30 points with Mathematics and Computing at Higher Level 6.

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

DDM

Relevant BTEC qualifications are accepted; please contact the Admissions Officer for further details.

Scottish Advanced Higher

A,B,B

including Mathematics and Computing plus excellent Highers for entry to Year 2.

Scottish HNC

Pass

HNC in relevant subject (including sufficient Mathematics at SCQF Level 6) with B in graded unit for entry to Year 1.

Scottish HND

Pass

HND in relevant subject (including sufficient Mathematics at SCQF Level 6 and Computing) with BB in graded units for entry to Year 1.

Scottish Higher

A,B,B,B

including Mathematics.

UCAS Tariff

114-152

We've calculated how many Ucas points you'll need for this course.

About this course


Course option

4.0years

Full-time | 2021

Subjects

Statistics

Mathematics

Artificial intelligence

This is an exciting, interdisciplinary programme that will give you broad foundations in Data Sciences. It involves all three main specialism of Heriot-Watt School of Mathematical and Computer Sciences, namely Mathematics, Statistics and Computer Science.

Data Sciences are at the core of the modern data analytics and engineering revolution, turning data into intelligence and information for decision-making and for solving complex, multi-faceted problems, in a rigorous and defensible way. It is a young discipline, and demand for expertise in all aspects of data sciences is growing very quickly, as the availability of data sets, and the need to interpret and use them, increases. Data Scientists are now in great demand in a wide variety of sectors that deal with the collection, analysis, interpretation, structuring and presentation of increasing large and rich data sets. Financial transaction, medical data, energy users, environmental samples are a few examples of large data sets now widely available. Because of this strong global demand, Data Scientist is frequently ranked as the no. 1 most promising job and consistently tops the best jobs rankings, with professionals in the field reporting high demand, high salaries, and high job satisfaction.

Because the BSc in Data Sciences programme is based on a strong mathematical and statistical foundation and emphasises large-scale data computation using the most relevant and up to date programming languages, graduates would be well placed to seek employment in any areas that require specific mathematical and computational abilities or could specialise further by pursuing postgraduate studies at the Master or PhD level. Depending on their interests, graduates may find employment in the areas of business, finance, government, science, transportation, forensics, energy, the environment or academic research

The first 3 years of the programme are designed to provide the necessary core skills and knowledge in mathematics, computer sciences, probability, statistics, machine learning and artificial intelligence. The fourth-year offers the option to focus on advanced machine learning, statistical algorithms and applications, data engineering, mathematical aspects of data structures, or applications to Artificial Intelligence.

This is one of the first BSc programme of its kind in the UK, truly interdisciplinary as well as truly global. The programme is offered in Edinburgh bur also Dubai and Malaysia, thus offering the widest possible options for studying abroad within the GoGlobal programme.

Level 1

Calculus (A and B), Software development (1 and 2), Discrete Mathematics, Introduction to Statistical Science, Praxis, plus one of Introduction to university Maths or Logic and Proof.

Level 2

Calculus and Real Analysis, Linear Algebra, Probability and Statistics (A and B), Data structures and algorithms, Database management systems, Software development 3 and Numerical Analysis A

Level 3

Statistical machine learning, Artificial intelligence and intelligent agents, Software engineering, advanced statistical methods, Bayesian inference and computational methods, Group project plus two of Ordinary differential equations, numerical analysis B, data visualisation analytics or statistical models B

Level 4

Optimisation, Data engineering pipelines, Big data management, advanced machine learning, plus a year-long dissertation and two optional courses from a pool of twelve courses in numerical analysis, stochastic processes, natural language processing with machine learning, data visualisation, advanced statistical and financial mathematics options, or mathematical biology.

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
£15,080
per year
International
£15,080
per year
Northern Ireland
£9,250
per year
Scotland
£1,820
per year
Wales
£9,250
per year

The Uni


Course location:

Edinburgh Campus

Department:

Computer Science

TEF rating:
Read full university profile

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.

86%
high
Statistics
86%
high
Mathematics

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.

Statistics

Teaching and learning

75%
Staff make the subject interesting
92%
Staff are good at explaining things
82%
Ideas and concepts are explored in-depth
84%
Opportunities to apply what I've learned

Assessment and feedback

Feedback on work has been timely
Feedback on work has been helpful
Staff are contactable when needed
Good advice available when making study choices

Resources and organisation

86%
Library resources
68%
IT resources
89%
Course specific equipment and facilities
91%
Course is well organised and has run smoothly

Student voice

Staff value students' opinions

Who studies this subject and how do they get on?

61%
UK students
39%
International students
61%
Male students
39%
Female students
71%
2:1 or above
2%
Drop out rate

Most popular A-Levels studied (and grade achieved)

A
A
A

Mathematics

Teaching and learning

77%
Staff make the subject interesting
94%
Staff are good at explaining things
84%
Ideas and concepts are explored in-depth
69%
Opportunities to apply what I've learned

Assessment and feedback

Feedback on work has been timely
Feedback on work has been helpful
Staff are contactable when needed
Good advice available when making study choices

Resources and organisation

90%
Library resources
72%
IT resources
87%
Course specific equipment and facilities
90%
Course is well organised and has run smoothly

Student voice

Staff value students' opinions

Who studies this subject and how do they get on?

74%
UK students
26%
International students
61%
Male students
39%
Female students
68%
2:1 or above
2%
Drop out rate

Most popular A-Levels studied (and grade achieved)

A
B
B

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?

82%
UK students
18%
International students
87%
Male students
13%
Female students
69%
2:1 or above
4%
Drop out rate

Most popular A-Levels studied (and grade achieved)

B
B
A

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.

Statistics

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.

£28,000
med
Average annual salary
98%
high
Employed or in further education
89%
med
Employed in a role where degree was essential or beneficial

Top job areas of graduates

64%
Business, research and administrative professionals
9%
Business, finance and related associate professionals
9%
Information technology and telecommunications professionals

The business and research sectors worry that the UK hasn't got enough people with good statistics skills, and as stats are at the heart of so much of the economy, and we only have a few hundred graduates a year in the discipline, this type of degree can be very useful and versatile. The finance industry is very popular with this group, and they're far more likely to be working in London than most other graduates. And who can blame them — statistics graduates starting work in London were earning an average of nearly £29k just six months after leaving university. There is also demand from the Scottish finance sector in Edinburgh and Glasgow - particularly in banking and insurance. But a good statistician can find work almost anywhere that data can be analysed - which, in an online world, is almost anywhere - and many industries struggle to find enough statisticians to fulfil demand, so stay flexible and you can find a variety of options.

Mathematics

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.

£25,000
med
Average annual salary
97%
high
Employed or in further education
80%
high
Employed in a role where degree was essential or beneficial

Top job areas of graduates

45%
Business, research and administrative professionals
21%
Business, finance and related associate professionals
7%
Sales, marketing and related associate professionals

Want to feel needed? This is one of the most flexible degrees of all and with so much of modern work being based on data, there are options everywhere for maths graduates. With all that training in handling figures, it's hardly surprising that a lot of maths graduates go into well-paid jobs in the IT or finance industries, and last year, a maths graduate in London could expect a very respectable average starting salary of £27k. And we're always short of teachers in maths, so that is an excellent option for anyone wanting to help the next generation. And if you want a research job, you'll want a doctorate — and a really good maths doctorate will get you all sorts of interest from academia and finance — and might secure some of the highest salaries going for new leavers from university.

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.

£25,000
med
Average annual salary
93%
med
Employed or in further education
78%
med
Employed in a role where degree was essential or beneficial

Top job areas of graduates

55%
Information technology and telecommunications professionals
8%
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.

Statistics

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

£29k

£29k

£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.

Mathematics

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

£29k

£29k

£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.

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

£25k

£29k

£29k

£35k

£35k

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.

Have a question about this info? Learn more here

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.

Have a question about this info? Learn more here

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.

Have a question about this info? Learn more here

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.

Have a question about this info? Learn more here

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

Have a question about this info? Learn more here

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