apprenticeship

Data Analyst Programme

Level 4 apprenticeship | Learner guide

Data without insight is noise. This programme builds the technical skills to turn data into answers, cleaning, modelling, visualising and communicating findings that actually change decisions.

Level

4

Duration

16 months + EPA

Standard

Data Analyst Apprenticeship

Min. OTJ hours

370

What this programme is for

This is La Fosse Academy’s technical Data Analyst programme, built for professionals in analytics, data engineering or data science roles who want to develop deep technical capability alongside the communication and governance skills that make analysis genuinely impactful.

It’s suitable for analysts working across any sector (technology, financial services, retail, healthcare, media, public services) where data is central to how decisions get made. You may be early in your data career or already working with complex datasets. This programme meets you where you are and builds from there.

You’ll leave able to work with large datasets, build robust models, create clear visualisations and communicate insight to stakeholders who need it. The technical depth is real. The application is immediate.

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 foundations

  • Data foundations, lifecycle and governance frameworks
  • Data collection, extraction and preparation using SQL, APIs and Python
  • Data cleansing, transformation and quality validation
  • Statistical analysis, hypothesis testing and inference
  • Machine learning foundations: supervised, unsupervised and evaluation

Analysis and communication

  • Data visualisation and storytelling with Power BI and Python libraries
  • Dashboard design for operational and executive audiences
  • AI-enhanced analysis and model deployment
  • Data ethics, privacy and responsible analytics
  • Communicating findings to technical and non-technical stakeholders

Core analytical tools

  • SQL (advanced querying, performance, window functions)
  • Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)
  • Power BI and DAX
  • Statistical modelling and inference
  • Machine learning: regression, classification, clustering

Visualisation and delivery

  • Power BI and Tableau for dashboard development
  • Jupyter Notebooks
  • Git and version control for data projects
  • A/B testing and experimentation frameworks
  • Spark and big data fundamentals

AI-enhanced capabilities

  • AI-assisted coding and data pipeline optimisation
  • Automated anomaly detection and data quality monitoring
  • Machine learning model explainability tools
  • Natural language processing for unstructured data
  • AI-driven insight generation and executive reporting

Programme specification

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Technical skills are built through practice. Every session uses real datasets and real analytical problems. You won’t be working on toy examples. You’ll be working on your organisation’s data, with tools your team actually uses.

Monthly workshops: live, interactive sessions. Technical content, real datasets and applied problem-solving from day one.

1:1 coaching: your Technical Coach is an experienced data professional. They’ll guide your analytical work, support your Python and SQL development and challenge your thinking.

Workplace data projects: analysis pipelines, dashboards, statistical models, governance reviews. Real analytical output from your own data environment.

Independent study: coding practice, technical reading and self-directed projects to deepen your skills between sessions.

Formal three-way progress reviews every 12 weeks

  • Written feedback on all work returned within 10 working days
  • Technical guidance on Python, SQL, modelling and visualisation applied to your data environment
  • Smart Assessor portfolio support against the Data Analyst KSBs
  • Mock EPA and targeted preparation before your assessment

Analysis outputs, data pipelines, dashboards, model documentation, OTJ logs and reflective accounts, all in Smart Assessor. Your coach feeds back in the platform. Your manager can contribute employer observations.

Skills England requires a minimum of off-the-job training hours for this apprenticeship. Your coach plans and records this with you from the start. OTJ activities include workshops, coaching, data projects, coding practice and EPA preparation.

The EPA is conducted by an independent EPAO. For Data Analyst it typically includes a work-based project report and presentation, and a professional discussion. Your project draws on real analytical work from the programme. At least one full mock with your coach before the assessment.

Where this takes you

Typical progression routes

Senior Data Analyst or Lead Analyst

Data Engineer or Analytics Engineer

Data Scientist or Machine Learning Engineer pathways

Business Intelligence Developer or Analytics Manager

Specialist roles in product analytics, growth or marketing data

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 build deep analytical capability?

Talk to the La Fosse Academy team.
Enquire now