Data Science BSc (Hons)



The first undergraduate Data Science course in Scotland, with built-in work experience.

Overview

Data Science is a new and rapidly expanding discipline that uses scientific approaches, business understanding, data and artificial intelligence to extract knowledge and understanding from the vast quantities of data sources that exist.

Data scientists work with data, including datasets relating to climate change, health and social media to enhance insight, to innovate and to enable data driven decision-making.

This course teaches you the the best way to learn about data science as it aims to teach you both the theory and practical elements of the subject: manipulating and analysing big data sets to draw meaning and understanding that affect our everyday lives.

From vast unstructured data to data organised as a warehouse, data is considered of strategic importance to governments, global organisations, health service providers, financial organisations, sporting organisations, educational institutions, the charity and voluntary sector and businesses in general.

Furthermore, career opportunities in the field of data are expanding, companies are looking at ways to develop technology through machine learning and data-driven analytics and require fresh talent to deliver ground-breaking results. The advantages of learning data science from undergraduate level is that you can master the fundamentals and gain that reward in the job market.

You will study a wide range of modules including data management, coding, statistical methods, data analytics, machine learning, artificial intelligence, data visualisation and data engineering.

Specialist courses are taught by expert staff who actively research applications of data science and you have an opportunity to undertake a data science research project in a topic that interests you.

This course was developed as part of the Edinburgh and South East Scotland CRD.

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Mode of Study:

Full-time

Duration:

4 years

Start date:

Sep

UCAS code:

G445

Course details

The course starts with a solid grounding in coding, statistics and foundation computing, including human-computer interaction and computer systems.

You will then learn about data engineering and analysis through database systems, data analytics and data visualisation.  

In years three and four you will further develop your skills in artificial intelligence and machine learning and undertake an Honours project linked to emerging topics in data science.


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    How you’ll be taught

     You will be taught through lectures and hands-on lab sessions.
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    Assessments

     You will be assessed through a mixture of practical assessments, reports, academic essays and exams.
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    Work placement

    A year long Work Based Learning module is available for this programme which can be undertaken in 3rd year which consists of 60 credits.

    In 2nd year, students attend timetabled Placement Preparation sessions which provides comprehensive information about sourcing a placement, tips for enhancing CVs, cover letters and interview preparation. A Student Futures Placement Coordinator is available to support students with their placement applications and approving placements as part of the course. Whilst on placement, students undertake work-related assessments alongside gaining valuable work experience. If this option is chosen, the course duration will be extended by one trimester.

    If students are not undertaking the yearlong placement, then there is a Group Project or the Professional Internship Module in Year 3 (one trimester) which gives students the opportunity to complete a project for an external client.

    Find out more about Computing Placements here.

Popular modules

Year 1

  • Foundations of Software Design and Development
  • Computer Systems
  • Information Systems in Organisations
  • Maths 
  • Scripting for Data Science
  • Introduction to Human Computer Interaction

Year 2

  • Fundamentals of Machine Learning
  • Database Systems
  • Operating Systems
  • Web Technologies
  • Software Engineering Methods
  • Algorithms and Data Structures

Year 3

  • Data Analytics
  • Artificial Intelligence
  • Interactive Data Visualisation
  • Computing in Contemporary Society
  • Advanced Database Systems
  • Group Project

Year 4

  • Advanced Machine Learning
  • Data Management and Processing
  • Computational Intelligence
  • Data Wrangling
  • Honours Project

Disclaimer

Study modules mentioned above are indicative only. Some changes may occur between now and the time that you study.

Full information is available in our disclaimer.

Entry requirements

What are the entry requirements for Data Science?

Our entry requirements indicate both Standard and Minimum qualifications with which we normally accept students. Competition for places varies from year to year and you aren't guaranteed a place if you meet the minimum qualifications.

Can you go straight into second year of university?

Advanced entry into Year 2 or Year 3 of this course is possible for students with suitable qualifications. See the individual year tabs for more information.

Can I make an appointment with an advisor to discuss further about the admission process?

If you want to get more information on the admission process, please get in touch with the undergraduate admissions team by submitting an enquiry form above.

Minimum Year 1

SQA Higher

Standard Entry Requirement: BBBB to include Maths or Physics. National 5 grade C in Maths OR Applications of Maths and English.

Minimum Offer Entry Requirement: BBCC to include Maths or Physics at grade B. National 5 grade C in Maths OR Applications of Maths and English.

You may be given an adjusted offer of entry if you meet our specified minimum entry requirements within our widening participation criteria, and outlined in our Contextual Admissions Policy. Click here for further information about our entry requirements and admissions policies.

A Level

  • BCC to include Maths (or Statistics) or Physics.
  • GCSE grade C/4 in Maths and English.

HNC/D

Unrelated HNC/HNDs may be considered

In addition, have Higher Maths (or Statistics) or Physics Grade B and National 5 English Grade C

Irish Leaving Certificate

  • H2, H2, H3, H3 at Higher Level to include Maths or Physics and grade O4 in Ordinary Level Maths and English.

BTEC (QCF) Extended Diploma Level 3

  • Minimum grades DMM (Distinction, Merit, Merit) in a related subject.
  • GCSE grade C/4 in Maths and English.

BTEC (QCF) National Diploma Level

  • Minimum grades D*D*

BTEC (QCF) National Diploma Level 3 plus A Level

  • Minimum grades DM (Distinction, Merit) and A Level grade C
  • GCSE grade C/4 in English and Maths.

International Baccalaureate Diploma

  • Award of Diploma with 28 points overall with three HL subjects at grades 6, 5, 4 to include Maths or Physics at grade 5.
  • Grade 4 in SL Maths and English.

European Baccalaureate

  • Pass at 70% or above with grade 7 in three subjects to include Maths or Physics.
  • Grade 6 in Maths and English.

T Levels

  • Merit - T Level with additional  A Level  in: Maths or Physics grade B 
  • GCSE Maths and English grade C/4

Minimum Year 2

HNC

Standard Entry Requirement: HNC – Pass HNC with A in the graded unit in Computing, Computer Games Development, Software Development, Data Science AND Higher Maths at Grade B for year 2 entry

Minimum Year 3

HND

  • Standard Entry Requirement: HND – Pass HND Data Science with a B in the graded unit AND Higher Maths at Grade B for year 3 entry.

If your first language isn't English, you'll normally need to undertake an approved English language test and our minimum English language requirements will apply.

This may not apply if you have completed all your school qualifications in English. Check our country pages to find out if this applies to you.

We welcome applications from students studying a wide range of international qualifications.
Entry requirements by country

Please note that international students are unable to enrol onto the following courses:
  • BM Midwifery/MM Midwifery
  • All Graduate Apprenticeship courses.

See who can apply for more information on Graduate Apprenticeship courses.

We’re committed to admitting students who have the potential to succeed and benefit from our programmes of study. 

Our admissions policies will help you understand our admissions procedures, and how we use the information you provide us in your application to inform the decisions we make.

Undergraduate admissions policies
Postgraduate admissions policies

Fees & funding

The course fees you'll pay and the funding available to you will depend on a number of factors including your nationality, location, personal circumstances and the course you are studying. We also have a number of bursaries and scholarships available to our students.

Tuition fees
Students from 2023/24 2024/25
Scotland £1,820 £1,820
England, Wales, Northern Ireland, and Republic of Ireland £9,250 £9,250
Overseas and EU £15,160 £16,680
Students from England, Wales, Northern Ireland, and Republic of Ireland will be invoiced the tuition fees for 3 years of their 4 years of study. The University offers a range of attractive Tuition Fee bursaries to students resident in specific countries. More information on these can be found here.
Please note tuition fees are subject to an annual review and may increase from one year to the next. For more information on this and other Tuition Fee matters please see Frequently Asked Questions about Fees Click this link for Information of Bursaries and Scholarships
If additional compulsory costs other than the tuition fees are applicable, these will be detailed in the course details.
Please note that the tuition fees liable to be paid by EU nationals commencing their studies from 1 August 2021 will be the Overseas fee rate. The University offers a range of attractive Tuition Fee bursaries to students resident in specific countries. More information on these can be found here.


Careers

What can you do with a degree in Data Science?

The BSc (Hons) Data Science degree at Edinburgh Napier University provides a comprehensive education in various skills and knowledge areas, allowing you to tackle real-world problems and extract insights from data to drive business decisions and innovation. You will learn about various programming languages and machine learning, as well as how to manipulate and analyse data. You’ll also learn how data can be visualised, how it’s managed within databases and how it’s kept safe through data ethics and privacy principles. You will also be equipped with communication, presentation, problem solving and critical thinking skills to help you make a real impact on your organisation. These various skills and knowledge areas will help you become a successful Data Scientist capable of solving real-world problems. 

There are many data science jobs available. With a data science degree you can expect to find employment in:

  • Data science
  • Software development
  • Data analysis
  • Systems analysis
  • Data engineering 
  • Machine learning engineering
  • Machine learning scientist
  • Statistician
  • Other opportunities in technology-focused organisations

What do Data Scientists do?  

As a Data Scientist, you will use your expertise in mathematics, statistics, programming, and domain knowledge to analyze large and complex datasets. You will explore data, identify patterns, and extract insights using statistical methods and visualization techniques.

You might also develop and apply machine learning models to make predictions, classify data, or uncover hidden patterns. On a daily basis, you may collaborate with teams, understanding business problems and framing them as data science challenges. Effective communication of findings through visualizations, reports, and presentations is also vital in a Data Scientist role.

You will deploy models into production systems, monitor their performance, and make necessary updates. Ultimately, data scientists leverage data to generate insights and support data-driven decision-making processes. Throughout your career you will continuously learn and stay updated with the latest advancements in the field.

Two students smiling as they study