Move your career forward and unlock new opportunities at work by studying for this industry-recognised, masters-level degree apprenticeship specialising in data analytics from a Russell Group university.
The digital workplace is a dynamic, innovative and rapidly changing environment and while working in the sector is an exciting place to be, keeping up with the pace of change as technologies evolve is challenging but essential for businesses and employees.
Our programme is designed to keep you at the forefront of your industry. Building on the foundations of your work experience, you’ll combine academic learning at degree level and on-the-job practical training to acquire the skills required by employers today and in the future. The programme will introduce you to specialist and strategic knowledge - with a strong focus on data analytics - that will enhance your understanding of key issues in business, technology, project and people management and allow you to consider these issues within the context of your workplace.
Our research-informed teaching will help develop your ability to investigate business data requirements and to carry out complex tasks including:
- applying data selection, data curation, data quality assurance and data investigation and engineering techniques
- provide advice and guidance to database designers and others in using the data structures and associated data components efficiently
- undertake data processing to produce data sets for study
- perform investigations using techniques including machine learning to reveal new business opportunities
- present data and investigation results along with compelling business opportunities reports to senior stakeholders.
By the end of the programme, you’ll be equipped to apply what you’ve learnt to your work and have the confidence to take on new challenges and responsibilities within your organisation.
Learning and assessment will take place over two years in your workplace as well as on campus at Queen Mary, University of London. This apprenticeship programme is the result of an innovative partnership between Queen Mary University of London, the Institute of Coding, and employers and we are seeking accreditation by Tech Partnership Degrees, which provides industry accreditation for digital and tech higher education that meet employer-defined standards.
Big Data Processing
Project Management for Big Data Analytics
Risk and Decision Making for Data Science and AI Project
You’ll need to have a 2:1 or above in BSc in Computer Science, Electronic Engineering or other Science discipline (e.g. Maths, Physics).
Candidates with great learning potential from other related areas (such as Economics) who can demonstrate relevant experience in Statistics/Programming will be considered on an individual basis, as well as candidates with a good lower second class degree. Applicants with unrelated degrees will also be considered if there is evidence of equivalent industrial experience. In the absence of a degree qualification, evidence of prior learning will be required.
For international applicants, we require English language qualifications IELTS 6.5 or TOEFL 92 (internet based).
Learning and teaching
The programme contains a mixture of campus-based and work-based modules.
The programme is delivered through 2 weeks of block teaching on Queen Mary campus during term-time, studying alongside degree apprentices from other employers and attending lectures, labs and tutorial sessions, practical and library-based research, presentations and group work.
For work-context modules, learning materials comparable to those for the equivalent campus-based module are provided, along with additional appropriate study guidance. Supplementary workshop-based or tailored individual support is provided through supervision by the module lecturer. You’ll be assigned an academic adviser/tutor, who is responsible for determining any additional individual/small group academic support needs, in conjunction with your employer.
Your project will be undertaken independently under the guidance of a project supervisor, who is an academic member of staff. They will advise on your progress, discuss research and design issues and plan your future work with you.
In order to enrol, you will need to be employed in a suitable role with a supporting employer who will pay your Queen Mary tuition fees.