The BSc Apprenticeship Data Science programme is developed as a three-way learning partnership between the student, the employer and the academic team. As a student, you will work full-time with your employer and study at Cardiff Met on a part-time basis, one day per week. Upon completion, you will gain a full BSc qualification from Cardiff Met, developing career-relevant skills and meeting regional skills gap.
Note: The BSc Apprenticeship Data Science recognises the
Higher Apprenticeship in Data Analytics Level 4 (currently delivered by
ALS Training) as a progression pathway for entry at Level 5 (Year 2) of the degree programme.
Evie is studying the BSc Apprenticeship Degree in Data Science at Cardiff Met while on placement with the Office for National Statistics (ONS). Here she takes us through a typical day:
Year 1 (Level 4):
- Principles of Programming
- Data Communication
- Fundamentals of Data Science
- Mathematics for Computing
Year 2 (Level 5):
- Visualisation of Data
- Object-Oriented System Design
- Applied Data Science
- Data & Knowledge Management
Year 3 (Level 6):
- Big Data & Distributed Computing
- Social Analytics
- Computational Intelligence
- Data Science Project
Certificate will be awarded upon successful completion of level 4 modules.
Diploma will be awarded upon successful completion of level 5 modules.
Degree will be awarded upon successful completion of level 6 modules.
Learning & Teaching
Developed as a three-way learning partnership, the programme will enable students to gain the in-demand skills needed to meet regional skills gaps. By utilising the full calendar year and applying core tenants of work-based learning, students will achieve their award within the same period as a standard full-time student, ensuring that the future skills needs of employers are met as effectively and efficiently as possible.
The programme outcomes have been designed by reference to and in compliance with the QAA Subject Benchmark Statement for Computing (2016), as well as referencing the QAA Framework for Higher Education Qualifications (2014).
The assessment strategy for the programme varies to ensure the most appropriate method for each specific module and subject area. Most modules are assessed through a combination of methods such as practical assignments, written assignments, technical reports, presentations, in-class tests, peer assessments and work-based placements. Students are also continuously assessed and given feedback on their progress and development throughout the year.
In addition, apprentices are expected to demonstrate professional competencies and behaviour within the workplace. A three-way learning plan is agreed between employer, apprentice and University, which details the on-the-job training and professional competencies (specific to each employer, such as working practices, company structure and processes, induction, and professional behaviour) the student needs to meet. Progress will be reviewed every two months as part of a joint industrial/academic progress update process.
How to Apply & Vacancies
Apprenticeship vacancies are advertised and handled by employers.
Students looking for more information about the BSc Apprenticeship Data Science and employers interested to enrol their apprentices or employees into this programme, please contact our
Centre for Work Based Learning Team:
Tel: 029 2041 6037 or 029 2020 5511