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BSc Applied Data Science Apprenticeship Degree

The BSc Applied Data Science Apprenticeship Degree programme is developed as a three-way learning partnership between the student, the employer and the academic team. The programme focuses on data, and builds apprentices’ ability to extract insights, knowledge and intelligence from the complex data points now ubiquitous in the world of business.

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 gaps.

Note: The BSc Applied Data Science Apprenticeship Degree 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 Applied Data Science Apprenticeship Degree at Cardiff Met while on placement with the Office for National Statistics (ONS). Here she takes us through a typical day:


Course Content

Over 3 years apprentices will study 4 modules per year progressing from academic levels 4 to 6.

Year 1 (Level 4):

- Principles of Programming
This module introduces the key principles and paradigms of programming, as well as the various stages of software development. It provides the apprentice with the basic skills and conceptual framework for developing useful and useable software.

- Data Communication
This module introduces apprentices to the theory and practice of data communication. The theory includes different approaches of domain analysis and visualisation principles, while the practice includes different approaches to presenting data.

- Fundamentals of Data Science
This module introduces apprentices to the basic skills of Data Scientists that include data cleaning, transformation, analysis and reporting using various industry standard software and programming languages, along with the ethics and legal issues relating to data.

- Mathematics for Computing
This module provides an introduction to the mathematical concepts underpinning the computing logics, exploring the theoretical and practical basis for the development and application of programming and data-driven techniques. It also develops learning skills for the future by facilitating a range of analytical solving skills, giving an awareness of the importance of those mathematical concepts in the modern world.

Year 2 (Level 5):

- Visualisation of Data
This module introduces the underpinning concepts for processing and analysing datasets and provides the apprentice with data visualisation and presentation skills essential for a data scientist.

- Object Orientated System Design
This module focuses on the development of useful and usable software systems using an appropriate programming paradigm, building on the importance of software carpentry and codemanship, including problem analysis, modelling, establishing requirements, designing, implementing and evaluating.

- Applied Data Science
This module introduces apprentices to the underpinning concepts for processing and analysing datasets of different types (structured/unstructured) and formats. The apprentice will learn to evaluate and apply different statistical methodologies, tools and techniques to solve data oriented real-life problems.

- Data & Knowledge Management
This module introduces students to the theory underpinning information, data and knowledge management. Students will learn to evaluate and apply the methodologies, tools and techniques used in the development of databases and the management and analysis of data, including relational, non-relational and next-generation technologies.

Year 3 (Level 6):

- Big Data & Distributed Computing
This module aims to provide skills to analyse big data on distributed environment. The module will focus on volume, variety, velocity of big data, along with a solid foundation in parallel and distributed computing principles underlying modern high performance computing platforms and tools.

- Social Analytics
This multidisciplinary module introduces apprentices to the importance of social media data, and the methods to analyse and visualise these unstructured data by quantitative and qualitative means. The module will also cover underpinning sociological concepts and how social media data can be used along with geospatial data for business intelligence purpose.

- Computational Intelligence
This module introduces the apprentice to the wide research discipline of computational intelligence. The apprentice will use specialist languages, software and development packages to investigate the application of computational intelligence to a wide range of problem domains.

- Data Science Project
This module allows the apprentice to apply what has been learnt throughout the course, and to demonstrate an ability to make valid judgements and to communicate them clearly within the Computer Science domain.

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 tenets 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.

Career Opportunities 

The course will provide apprentices with the necessary skills and knowledge to understand, apply and critically evaluate underlying Data Science principles. In addition, apprentices will also be equipped with the skills to design and utilise Data Science systems and use industry standard tools and techniques in their implementation.

Apprentices will be ably equipped to pursue a highly lucrative career. According to Glassdoor.co.uk, Data Scientist is the 7th best job with a median base salary of £46,000 and an excess of 2000 job opportunities across the UK (data as of October 2019). 

Due to taking the apprenticeship route, apprentices who graduate from the scheme will also have three years of valuable work experience at the point of graduation, providing them with an excellent springboard to future success. 


The Welsh Government is funding places on the programme, meaning that there is no cost for tuition fees to the company or the apprentices (standard tuition fees would be £9,000 per annum). All that will be required is day release to allow the apprentice to attend University, alongside providing the opportunity for learning experiences on the job.

Entry Requirements 

 Five GCSE passes including English Language and Mathematics at Grade C or above, or grade 4 or above for those studying newly reformed GCSEs in England. Plus, any one of the following: 

• 96 points from at least 2 A-Levels to include grades CC, Welsh Bacc to be considered alongside this as a third subject. 

• BTEC National Extended Diploma with grades MMM 

• 96 points from at least two Scottish advanced highers to include grades DD 

• 96 points from the Irish Leaving Certificate at Highers to include 2 x H2 grades. Higher level subjects only considered with a minimum grade H4 

• 96 points from the Access to Higher Education Diploma

• A related apprenticeship at level 4. The Higher Apprenticeship in Data Analytics Level 4 is recognised as a direct entry to Level 5 of the programme.

How to Apply & Vacancies

Apprenticeship vacancies are advertised and handled by employers.

Current Data Science Degree Apprenticeship vacancies with the Government Statistical Service

Contact Us

Potential apprentices looking for more information about the BSc Applied Data Science Apprenticeship Degree and employers interested to enrol their apprentices or employees into this programme, please contact Tara Williams, our Degree Apprenticeships Lead:
Email: apprenticeships@cardiffmet.ac.uk or prentisiaethau@cardiffmet.ac.uk