apprenticeship
What this programme is for
Level 7 is degree equivalent. This programme is for senior data and AI professionals who combine deep technical expertise with the strategic thinking and leadership skills to drive organisational transformation through data.
It’s suitable for professionals already working at a high level in data science, AI engineering, analytics leadership or applied research, across financial services, technology, healthcare, government, retail and any data-intensive sector. You may be a data scientist moving into strategic AI roles, a technical leader looking to formalise expertise at the highest level, or a specialist in a particular domain of AI who wants broader capability.
At 20 months and Level 7, this programme expects intellectual rigour, research capability and the ability to operate in ambiguous, complex problem spaces. You’ll graduate with expertise that positions you at the forefront of the data and AI profession.
What you'll cover
The programme covers all the knowledge, skills and behaviours required for the End-Point Assessment, built around real challenges in your organisation.
Technical depth
- AI and data science foundations: ML techniques, NLP and computer vision
- Data engineering, pipelines and scalable architecture
- Advanced analytics, statistical modelling and experimentation
- Data product development and iterative delivery
- Ethics, governance, bias mitigation and responsible AI
Strategy, leadership and communication
- Communication, stakeholder engagement and data storytelling
- Research methodologies, hypothesis testing and innovation
- AI strategy, leadership and organisational impact
- Advanced AI application: APIs, automation, real-time systems and deployment
- Emerging AI techniques and keeping current in a fast-moving research landscape
Core AI and data tools
- Python (advanced: PyTorch, TensorFlow, JAX, Hugging Face)
- Large language models: fine-tuning, RAG and deployment
- Computer vision: CNNs, object detection and segmentation
- Statistical modelling: Bayesian inference, causal analysis
- Experiment design, A/B testing and causal inference
MLOps and architecture
- Cloud ML: AWS SageMaker, Azure ML, Vertex AI
- MLOps and model lifecycle management
- Feature stores and data versioning
- High-performance computing and GPU workloads
- Data architecture: lakehouses, warehouses and streaming systems
AI-enhanced capabilities
- AutoML for hyperparameter optimisation and model comparison
- AI-driven feature engineering and pipeline generation
- Bias detection, explainability and fairness evaluation frameworks
- Automated MLOps monitoring, drift alerting and retraining triggers
- AI-supported governance oversight and regulatory risk identification
Programme specification
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At Level 7, this is professional development at the highest level. Sessions are designed for senior practitioners who are already doing complex, consequential work. The emphasis is on depth, intellectual challenge and research-grade rigour.
Monthly workshops: live, technical sessions. Advanced AI and data content, research discussions and peer learning from practitioners working across different domains and sectors.
1:1 coaching: a senior AI and data practitioner. They’ll work at the level you operate at, supporting your research, your production systems and your strategic thinking across the full 20 months.
Workplace AI and data projects: production AI systems, data products, strategic analyses, research investigations. Real work that demonstrates strategic impact and technical depth.
Research and independent study: reading papers, engaging with the research community and building theoretical depth through self-directed learning. At Level 7, this is a core expectation of the programme.
A senior AI and data practitioner with strategic as well as technical expertise. The coaching relationship at Level 7 is a professional dialogue, your coach will challenge your thinking, push your research and support your leadership development alongside your technical work. They will:
- Conduct formal three-way progress reviews every 12 weeks
- Mark all work and return written feedback within 10 working days
- Support your AI systems development, data strategy work and responsible AI practice
- Build and review your Smart Assessor portfolio against the AI and Data Scientist KSBs
- Prepare you for your End-Point Assessment with mock assessments and strategic presentation coaching
AI system documentation, research outputs, data product write-ups, strategic analyses, governance assessments and OTJ logs, all in Smart Assessor. At 20 months and Level 7, building evidence from day one and maintaining rigorous documentation throughout is essential.
Skills England requires a minimum of off-the-job training hours for this apprenticeship. Given the 20-month duration and Level 7 depth, structured OTJ planning is essential from the start. OTJ activities include workshops, coaching, AI and data projects, research and writing, conference attendance and EPA preparation.
The EPA is conducted by an independent EPAO. At Level 7, it typically includes a substantial work-based project report demonstrating advanced AI and data science capability with strategic impact, a presentation and a professional discussion. Your project must demonstrate real AI or data systems built and deployed with measurable organisational value.
Your coach prepares you with at least one full mock assessment. At Level 7, presentation quality and the ability to discuss your work at a strategic and technical level both matter significantly.
Level 7 apprenticeships require a degree or equivalent prior learning, or significant demonstrable experience at an equivalent level. You need to be in a senior AI or data science role with your line manager’s support. Both of you sign a Commitment Statement at enrolment confirming your agreement to the programme requirements.
Where this takes you
A Level 7 qualification. A portfolio demonstrating strategic AI and data leadership. That positions you at the very top of the data and AI profession.
Typical progression routes
Head of Data Science, Head of AI or Director of Data
Chief Data Officer or Chief AI Officer pathway
Principal Data Scientist or Distinguished Engineer
AI Research Lead or Applied Research Director
Independent consulting or advisory roles in AI strategy
Your onboarding journey
Here's what to expect before your learning begins.
1
Pre-enrolment
Expression of interest
Application form
2
Initial assessment
Online maths and English check
Diagnostic skills review
3
Enrolment
Sign Commitment Statement
Submit documents
4
Induction
Attend induction workshop
Set up Smart Assessor
5
Final onboarding
Compliance check
Programme begins
Ready to lead at the frontier of AI and data?
Talk to the La Fosse Academy team.
Enquire now