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L7Apprenticeship5611 approved provider
The Level 7 Artificial intelligence (AI) data specialist, and the 1 provider delivering it.
Discover new artificial intelligence solutions that use data to improve and automate business processes.
About this apprenticeship
What this apprenticeship covers
Apprentices learn to design and build AI solutions that address complex, large-scale business problems where conventional analytical methods fall short. The programme covers applied research methods, machine learning, and data governance, alongside the ethical frameworks that shape responsible AI deployment. Apprentices gain the technical depth to work with high-volume, high-velocity, and highly varied datasets, and develop the communication skills needed to translate findings and recommendations to both technical peers and senior non-technical decision-makers.
Day-to-day responsibilities
Working at a senior technical level, apprentices lead research into AI applications, develop and test machine learning models, and collaborate with data engineers, scientists, and analysts to maintain quality standards across AI solutions. They engage regularly with product managers, heads of data, and directors to align technical work with business objectives. Typical outputs include research findings, model documentation, governance reports, and recommendations for adopting new tools or processes. External engagement with regulators, academic researchers, or partner organisations is also part of the role in many settings.
Career outlook
Completion typically leads to roles such as Machine Learning Engineer, AI Specialist, or AI Strategy Manager, with progression towards Director of AI or Chief Data Architect in larger organisations. The occupation is genuinely cross-sector: employers range from NHS trusts and financial services firms to manufacturing businesses, logistics operators, and government bodies. Because this is a Level 7 programme aimed at applied research and technical leadership, most completers move into positions with significant strategic influence over how their organisation uses data and automated systems.
1 approved provider
Sorted by achievement rate.
Cambridge Spark
Employer: 4.0
Cambridge Spark is a specialist data and AI training provider that helps corporate and government or...
Career outcomes
Roles after completion
Completers typically move into roles such as Machine Learning Engineer, Artificial Intelligence Engineer, AI Specialist, or AI Strategy Manager. Some move directly into applied research positions within data or technology functions, taking ownership of machine learning pipelines, model development, and the deployment of AI solutions at scale. The level 7 standard positions graduates for roles with a degree of technical authority from day one, rather than purely junior individual contributor positions.
Progression paths
Within three to five years, many practitioners advance to Senior Machine Learning Engineer, Lead AI Engineer, or Principal Data Scientist. From there, the paths diverge: a deep-specialist track leads toward roles such as AI Research Scientist or Chief Data Scientist, focused on model architecture and applied research. A leadership track moves toward Head of Data, AI Programme Director, or Director of AI, carrying responsibility for organisational AI strategy, team management, and governance frameworks. Both tracks appear across large organisations and fast-growing technology businesses.
Where these roles sit
Employers hiring at this level span a wide range of sectors, including financial services, healthcare, retail, defence, utilities, and central and local government. Both private organisations and public sector bodies, such as NHS trusts and government departments, recruit for these roles. Employer size tends toward large organisations with substantial data infrastructure, though specialist consultancies and scale-up technology firms also hire AI professionals at this seniority. Demand is consistent across England's major city regions.
How it's assessed
How the apprenticeship is assessed
Learning takes place entirely within employment, with the apprentice applying knowledge of machine learning, data modelling, AI ethics, and applied research to real business problems throughout the programme. Before final assessment, the apprentice and employer confirm readiness at a gateway point, which typically involves checking that the required knowledge, skills, and behaviours have been demonstrated to the required standard. Final assessment then confirms whether the apprentice can perform at the level expected of a specialist operating with technical authority in an AI and data context. Assessment models for many Level 7 standards are currently being updated; check the standard's gov.uk page for the current specification.
What learners need to prepare
Building a strong body of workplace evidence from the start of the programme makes the assessment process considerably more manageable. Apprentices should document applied research, project outcomes, and decisions made throughout, rather than attempting to reconstruct evidence later. Regular reviews with both the employer and training provider will help track progress against the knowledge, skills, and behaviours set out in the standard. Because this occupation involves independent technical leadership, being able to articulate reasoning and methodology, not just results, will be central to demonstrating competence.
Choosing a provider
What good looks like
Providers worth considering will have an achievement rate above 65% for this standard, though given the small cohort sizes typical at Level 7, treat that figure alongside apprentice satisfaction scores and written reviews. For a role this technical, the curriculum should visibly track current practice: look for explicit coverage of large language models, MLOps pipelines, responsible AI frameworks, and data governance regulation including the UK GDPR. Strong providers will have tutors with active industry backgrounds, not just academic credentials, and will be able to point to alumni working in machine learning engineering or AI strategy roles.
Red flags to watch for
Be cautious of providers with high enrolment numbers but vague answers about how they keep curriculum content current. At Level 7, a provider who cannot name the AI frameworks and tools taught, or who describes delivery in generic terms about "problem-solving" and "critical thinking," is unlikely to keep pace with a field moving this quickly. Opaque end-point assessment preparation is also a concern. If employer satisfaction scores are low or absent, that suggests the provider is not engaging meaningfully with the organisations actually using the apprentices day to day.
Questions to ask before you commit
- Which AI frameworks, platforms and tools are explicitly covered in the curriculum, and how recently were they updated?
- How do your tutors maintain current industry knowledge, and what are their professional backgrounds outside teaching?
- Can you show examples of projects apprentices have completed, and what roles did graduates move into?
- How do you handle the research and applied project elements, and what support is available for apprentices working on novel business problems?
- What is your achievement rate specifically for this standard, and what is the typical cohort size?
- How do you structure employer engagement throughout the 24 months, beyond the initial sign-up?
- What guidance do you provide on AI ethics and data governance, including alignment with current UK regulatory expectations?
Common questions
Who is eligible to apply for this apprenticeship, and what background is typically expected?
Applicants must be employed and have the right to work in England. At level 7, employers and providers typically expect a degree or equivalent professional experience in a quantitative or technical field such as computer science, mathematics, statistics or engineering. Strong programming skills and prior exposure to data analysis or machine learning are commonly required. Entry criteria vary by provider, so check directly with your chosen training organisation for their specific requirements.
How long does this apprenticeship take, and how does learning fit around work?
The typical duration is 24 months, though the actual minimum may differ depending on current funding rules. The apprentice remains employed throughout and applies learning directly to their day-to-day role. A portion of contracted hours must be spent on off-the-job training, but the exact percentage is subject to ongoing reform. Check the current apprenticeship standard on gov.uk for the up-to-date specification before planning your programme.
How is the apprenticeship assessed, and what does the end-point assessment involve?
Before reaching end-point assessment, the apprentice must pass through gateway, where the employer, apprentice and training provider confirm that the required knowledge, skills and behaviours have been developed. Assessment models for many standards are being reviewed as part of current Skills England reforms. The apprentice must demonstrate genuine occupational competence. For the current assessment plan and methods, refer to the standard's page on gov.uk.
How does an employer pay for this apprenticeship, and what does the funding band mean?
The funding band for this standard is £17,000, which is the maximum government contribution toward training and assessment costs. Larger employers with an apprenticeship levy account draw down from their existing levy pot. Smaller employers who do not pay the levy co-invest with government, typically contributing 5% of the training cost with government paying the remainder. Employers taking on an apprentice aged 16 to 18 who have fewer than 50 staff pay nothing toward training costs.
What does an AI data specialist apprentice actually do during the working day?
Day-to-day work involves building and refining machine learning models, conducting applied research on large or complex datasets, and developing AI solutions to automate or improve business processes. Apprentices work alongside data scientists, engineers and senior leaders, presenting technical findings to non-technical stakeholders. They contribute to setting technical standards, identify where AI can create business value, and stay current with data governance frameworks and ethical guidelines relevant to their organisation's sector.
What career progression is available after completing this apprenticeship?
Graduates of this programme typically move into senior technical or strategic roles. Common destinations include machine learning engineer, AI specialist, AI strategy manager and director-level positions overseeing data and AI functions. The level 7 qualification also provides a strong foundation for doctoral research or fellowships for those interested in academic or research pathways. Because the occupation spans virtually every sector, progression opportunities exist in industry, public services, academia and policy organisations.
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Curated by Alex Lockey, FATP founder and editor. Last reviewed: .
Sources include the apprenticeship's official specification on apprenticeships.gov.uk, Skills England guidance, IfATE archive records, DWP funding bands, and provider data sourced directly from the public Apprenticeship Provider and Assessment Register (APAR). Standard reference: 561.
Some sections on this page were drafted with AI assistance from published source data and reviewed by a human editor before publication. See our editorial methodology for how we maintain this content. Spotted something out of date? Tell us.
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