Data Science (Graduate Apprenticeship) BSc (Hons)

Enhance your knowledge, gain practical skills, and launch your career and in the emerging field of Data Science and Artificial Intelligence


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.

The BSc (Hons) Data Science Graduate Apprenticeship will equip you with the skills, knowledge, and behaviours to make a valuable contribution in one of Scotland’s most in-demand skill-sets. You will enhance your skills and improve your career prospects in the emerging field of Data Science by studying for a fully-funded university degree while in a paid, relevant job role.

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. Throughout, you will obtain the requisite underpinning of technical knowledge, combined with key capabilities in data governance and the application of ethics, with a focus on well-rounded professional skills and behaviours.

Companies are increasingly looking at ways to develop technology through machine learning and data-driven analytics and require fresh talent to deliver ground-breaking results. You will be taught 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. You can then apply your learning immediately in the workplace to solve real-world problems, allowing you to accelerate your career, and your employer to have the most up-to-date skills in their business.

Our Graduate Apprentices will typically initially work in job roles such as Data Analyst, Document Controller, Data Coordinator, Business Intelligence and Finance/Calculations Analyst. They may also be in more senior level roles within IT more broadly, but looking to enhance their Data Science skills. You will not be expected to undertake a data related role right away, but should aim towards working in this area as you progress into the latter stages of the course. This should be supported by your employing organisation.

Successful graduates from this course have gone onto enhance their careers and progress through their company in areas such as:

  • Data science
  • Software development
  • Data analysis
  • Systems analysis
  • Data engineering 
  • Machine learning engineering
  • Machine learning scientist
  • Statistician
Student looking through interactive glasses

Mode of Study:



4 years

Course details

As a Graduate Apprentice you will study for your degree alongside your job, spending approximately 80% of your time in work and 20% in university. This unique combination offers an integrated experience, where practical skills and knowledge gained during the university days can be embedded in your working practices. Skills learned directly in the workplace are aligned with and can be applied to coursework and assessment. This allows you to attain an honours degree in 4 years, the same time as traditional full-time students.

You will develop abilities across the core and emerging areas of data science including statistical techniques, data analytics, data engineering, as well as machine learning and artificial intelligence. You will gain the requisite underpinning technical knowledge combined with key capabilities in data governance and the application of ethics, and well-rounded professional skills and behaviours.

A key part of the Data Science GA is that each of the eight key content areas are combined to deliver a holistic learning experience. These are:

  • Data Management
  • Data Analytics
  • Statistical Techniques
  • Machine Learning and Artificial Intelligence
  • Data Engineering
  • Business Insights Through Data Science
  • Data Protection and Ethics
  • Data Science Professional Skills and Behaviours

As you progress through the course, more of your job role will be used to gain credit towards your final award. This is captured in the Professional Practice modules which allow us to personalise your learning to ensure it meets your needs, those of your employing organisation and the university.

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    How you’ll be taught

    This Graduate Apprenticeship is taught over 4 years at our School of Computing, Engineering and Built Environment, based in our Merchiston Campus in Central Edinburgh. It is delivered across three trimesters over a full calendar year on a day release basis. You attend classes one day per week, in years 1 and 2, studying 2 modules per day. Professional Practice modules are work based and timetabled in the summer trimester, for which there is no on-campus requirement, offering greater flexibility. In years 3 and 4 the emphasis on work-based learning increases and on-campus teaching is significantly reduced.

    Your work-based learning will be overseen by a workplace mentor and university coach. You will be offered tripartite progress review meetings each trimester to support you in your work and studies.

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    A mixture of practical assessments, reports, academic essays and exams. You are also assessed on your learning in the workplace, primarily in the summer trimesters. As you progress through the course, more of your job role is used to gain credit towards their final award through Professional Practice and your final-year dissertation.

    The assessments will allow you to demonstrate your application of the knowledge and skills you are gaining both though your studies and through your work experience.

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    Work placement

    You will be a full-time employee for the duration of the programme.
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    Graduate apprentices can enjoy the same full access to our campus facilities as a full-time student. All learning takes place at our Merchiston campus, which is centrally located in the heart of Edinburgh. Merchiston campus is home to our creative, computing and engineering students.

    Facilities include modern classrooms and cutting-edge labs. Our Merchiston Library is a bright attractive environment providing both silent and collaborative study spaces designed to suit a variety of learning styles. In addition, Merchiston boasts a business incubator, two cafes and a 500-seat computing centre, with both Mac and PC hardware, that is open 24hrs a day in Trimesters 1 and 2.

Popular modules

Year 1

  • Foundations of Software Design and Development
  • Mathematics for Software Engineering
  • Data Science with Python
  • Introduction to Human Computer Interaction
  • Computer Systems
  • Professional Practice 1: Work-Based Project

Year 2 

  • Object Oriented Software Development
  • Database Systems
  • Algorithms and Data Structures
  • Web Technologies
  • Professional Practice 2: Work –Based Project

Year 3

  • Data Analytics
  • Interactive Data Visualisation
  • Professional Practice 3: Work-Based Project

Year 4

  • Machine Learning for Conversational AI
  • Information Security and Society
  • Data Management and Processing
  • Honours Project: Work-Based Project


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

This programme is available to new and existing employees who work and reside in Scotland. Entry requirements cater to professionals and can account for both academic and work-based experience. You need to be employed with a supporting organisation to be eligible, and must have a job within the same field as your chosen subject area.

All applicants must:

  • Be 16 or older (some employers may require 18+)
  • Have the right to live and work permanently in the UK
  • Have ordinary residence in Scotland
  • Meet programme entry requirements

Advanced Entry

Advanced entry into Year 2 or 3 is possible for students with suitable qualifications. If applying for advanced entry, you will need to provide sufficient evidence of qualifications and experience through our process of Recognition of Prior Learning (RPL). Applications are considered on an individual basis.

Work Experience and Professional Qualifications

We encourage applications from individuals whose work experience or professional qualifications provide them with a comparable foundation for starting the course. You will be considered through our Recognition of Prior Learning (RPL) process and asked to provide evidence of relevant work experience through a detailed CV or application form, including an employer reference. Advanced entry may also be granted if you have sufficient industry-related experience and qualifications.

Usually, unrelated work experience is not considered sufficient for entry without meeting the minimum academic entry requirements.

Foundation and Modern Apprenticeships

We offer enhanced recognition for Foundation and Modern Apprenticeships if you are applying to a Graduate Apprenticeship in a similar subject area. Please refer to our typical entry requirements for more information on each course.

Already have a degree or similar qualification?

You could apply for funding for a Graduate Apprenticeship in a similar subject area if your existing qualification is at a lower level. You may also be eligible for funding if you have completed a degree in a different subject area. For example, if you recently completed a Biology Honours degree, you can still apply for a Civil Engineering Graduate Apprenticeship.

You are not eligible to apply for a Graduate Apprenticeship if you have completed a similar degree within the past 5 years.

To meet our Standard Entry Requirements you must have EITHER:

  • Four SQA Highers at Grade BBBB (or equivalent) including Maths, Statistics or Physics. National 5 grade C in Maths/Lifeskills Maths/Applications of Maths and English are required if not taken at Higher
  • A Foundation Apprenticeship in IT: Software Development at SCQF Level 6 plus two SQA Highers at Grade BB
  • A Modern Apprenticeship at SCQF Level 6-7 in an ICT/Digital related discipline
  • HNC or HND in an unrelated discipline plus Higher Maths, Statistics or Physics at Grade B
  • Sufficient recognition of prior learning (RPL) through industry-related experience, qualifications, and informal learning. RPL applications are considered on an individual basis

Our Minimum Offer Entry Requirement: BBCC. National 5 grade C in Maths/Lifeskills Maths/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.

To meet our year 2 entry requirements you must have EITHER:

  • A Modern Apprenticeship in a related discipline at SCQF Level 8
  • An HNC at Grade A in a related discipline such as Computing, Computer Games Development, Software Development, Data Science AND Higher Maths at Grade B
  • An HND at Grade B in a related discipline, such as the above
  • A minimum of two SQA Advanced Highers at Grade BB (or equivalent) including Computing
  • Sufficient recognition of prior learning (RPL) through industry-related experience, qualifications, and informal learning

To enter this programme at the start of Year 3 you must have 240 SCQF credits (or equivalent) of which a minimum of 120 credits are at SCQF 8 (or equivalent) AND/OR significant recognition of prior learning (RPL) through industry-related experience, qualifications, and informal learning.

SCQF Level 8 qualifications can include:

  • HND at minimum Grade B in Data Science in the graded unit AND Higher Maths B
  • Diploma for Higher Education in Data Science or Computer Science
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.


As a Graduate Apprentice you are fortunate to be studying for your honours degree alongside your work-based apprenticeship position and to have the support of both Edinburgh Napier staff and your workplace. You are first and foremost an employee for your organisation, and therefore could develop your career through your entire apprenticeship journey. Your employer will look for opportunities for you to apply your learning in work and develop as a professional, meaning you may be offered career progression opportunities at any time during your studies.

here 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.