BSc (Hons) Digital and Technology Solutions (Data Science)


New degree apprenticeship programme in Data Science from an award-winning teaching team in partnership with some the UK’s leading professionals.

The program is an apprenticeship and as such requires employment and quality work based learning experience, supplemented with a blended learning approach to content delivery. The content will be delivered through a combination of video lectures and tutorials, webinars, online discussion groups, online materials, and class attendance.

The apprenticeship includes and develops knowledge and skills in the following areas:

  • Computer programming
  • Networks and security
  • Operating systems
  • Project management
  • Professional practice and law
  • Probability and statistics
  • Machine learning
  • Big data engineering and applications
  • Natural language processing
Treforest Maths and Data Science PT Degree Apprenticeship 2021 56 Months

The course does not operate in a typical undergraduate mode, as the students take approximately 18 calendar moths to achieve a full level of study, with it being four and half years in duration, part-time.  

The course has been designed to provide an introduction and further learning within the areas of applied computing and Data Science.  The final year sees more focus upon Data Science as a specialism where the majority of the level is spent to study this area in addition to the apprentices undertaking a major project.  

Level 4

  • Principles of Computer Programming
  • Computer Systems and Network Technologies
  • Professionalism and Employability Running
  • Information Management, Assurance and Security
  • Fundamentals of Probability and Statistics
  • Principles of Data Science

Level 5

  • Project management and professional practice
  • Secure software development
  • Operating system theory and implementation
  • Industry led project
  • Fundamentals of Machine learning
  • Advanced probability and statistics

Level 6

  • The computing professional in practice
  • Advanced machine learning
  • Big data engineering and applications
  • Natural language processing
  • Capstone project


The course is delivered both on site and also by blended/distance learning which are supported through tutorial sessions on campus.  This allows the student to study flexibly, but also receive the levels of support that they require.  There is also a “boot camp” in the first year to bring everyone up to speed intensively delivered at our Treforest campus. 

Typically, students physically attend campus every third Friday, whilst learning continues at their place of employment.  Students are encouraged to visit campus and its support facilities in addition to this and are welcome to meet with any member of the course team, either physically or electronically, should this be needed.


The course is made up of modules that have either assignment based, examination-based, presentations, individual and/or group work and portfolios at the heart of the assessment process.  The type of assessment will depend upon the module.


At the School of Computing we have industry leading faculties, these would be in addition to any role specific software and platforms that you would have access to through your employer.



Students are mentored at both the institution and also through a workplace mentor.  Regular tripartite meetings are held between all parties to ensure every chance of success and achievement.  Mentors are key and form a part of the course management team and are informed of any changes or issues surrounding the course.

The employer and university will seek to advertise widely, and USW will promote this programme through its network of FE partners as well as by the employer through public advert. We will seek to promote awareness of degree apprenticeships in this sector as an option via our schools and colleges outreach and local partnerships. 

We will work with the employer and our FE network to explore outreach to Schools and Colleges and the development of future progression pathways from lower level apprenticeships. The arrangements for admissions will seek to ensure equality of opportunity for all applicants. It is expected that anyone admitted to the course should be able to fulfil the objectives of this particular course and achieve the required standard. Evidence will be required that applicants are able to meet the demands of the course. 

Typical A-Level Offer 

BCC - CDD (this is equivalent to 104-80 UCAS tariff points). 

Typical Welsh BACC Offer 

Pass the Advanced Welsh Baccalaureate Diploma with Grade C/D in the Skills Challenge Certificate and BC - CD at A Level (this is equivalent to 104-80 UCAS tariff points).

Typical BTEC Offer

BTEC Extended Diploma Distinction Merit Merit - Merit Merit Pass (this is equivalent to 112-80 UCAS tariff points).

Typical IB Offer

Pass the International Baccalaureate Diploma with higher grades of between 655-445 (this is equivalent to 112-80 UCAS tariff points)

Additional Requirements

GCSEs: The University normally requires a minimum 5 GCSEs including Mathematics and English at Grade C or above, or their equivalent but consideration is given to individual circumstances 

Equivalent international qualifications are acceptable. In general, international applicants will need to have achieved an overall IELTS grade of 6.0 with a minimum score of 5.5 in each component.

Those without such qualifications are considered on an individual basis and a wide range of prior experience may be taken into account. Consideration for RPCL, RPEL and work-based learning is available within University procedures. In each case, entry is judged on a reasonable expectation of the applicant successfully completing the course.

The company offering an apprenticeship will coordinate the recruitment process, in the case of Capgemini the process is outlined here:

If the application for a Degree Apprenticeship is shortlisted, they will be asked to complete an online Situational Strength Test to ascertain the applicant’s cultural fit. If they are successful, the next stage will be a Digital Interview which is a combination of written and video recorded questions. Next, they will be invited to an assessment centre on-site, consisting of an interview, micro exercises and a group exercise.


You will receive an education and an experience of the industry that is second to none.   Not only will you study with an award-winning team of academics, but also you will work with ultra-professional and experienced people in your workplace who will also mentor and develop you as you progress.

Possible job roles that you can land after graduating may include:

  • Graduate data scientist
  • Data analyst
  • Data engineer
  • Machine learning engineer


To undertake this course, you will need to have secured a position within one of our partner organisations.  Or be employed and have the support of your employer.  Opportunities to join this course are advertised through the company pages, Careers Wales, USW and other outlets.  

You will need to apply and be selected by an employer or be put forward by an existing employer to begin study.  This sounds challenging, but a successful applicant will have a job, the opportunity to develop their skills within a professional working environment surrounded by industry professionals and, the opportunity to study for a degree qualification.  

The course fees are covered as a part of this programme.  You will earn a salary that is provided and agreed by the employer. So, it’s a win/win situation; no student fees, a job and a regular income!

Our work-based learning opportunities offer many benefits to students and employers, large and small.

To discuss the range of apprenticeship opportunities at USW, or if you would like a member of our team to evaluate your work-based learning needs, contact us on 01443 482203 or at [email protected].

All places are awarded following a recruitment process that is specific to the participating company or organisation.  All places are subject to obtaining a role within such a company or organisation and meeting the institutions entry requirements.