Level 4 Data Analyst Apprenticeship

One data apprentice can create real business impact

£1.4m revenue identified through data-driven insights

£1m cost savings by identifying inefficiencies

90% shorter project times achieved through automations

100% time saving on data cleaning and preparation

Deliver on your data analytics strategy

Build the data analytics capability you need to maintain your competitive advantage and increase productivity across your organisation. Over the duration of the programme, Cambridge Spark's Level 4 Data Analyst Apprenticeship equips employees with the skills to apply data analytics in the workplace.

From day one, we teach Python - the most popular programming language for data analytics and key for maximising the impact of data analysis. The programme builds competence with essential Python libraries including Pandas and Numpy, data visualisation tools like Seaborn and matplotlib, working on databases with SQL and testing code in a production environment.

The Curriculum

Our curriculum is developed by our leading faculty, composed of data scientists in leading industry positions and academics from some of the top universities in the world. Our curriculum is continuously updated and reiterated to incorporate the latest skills. Our programme includes the core modules, elective modules for learners wishing to pursue specialist areas, as well as monthly Industry Insight sessions delivered by leaders from different sectors.

Core Modules

Introduction to Python and Pandas

Explore Python and Pandas to leverage Python's popularity and Pandas' powerful tools for essential data analysis tasks.

Data Science for Business

Apply data science to solve business problems with data analysis techniques, considering ethics and emerging legislation.

Further Python and Pandas

Develop proficiency in Pandas to efficiently manipulate and process data, enabling advanced data visualisation and modelling techniques for real-world applications.

Data Visualisation

Develop proficiency in Pandas to efficiently manipulate and process data, enabling advanced data visualisation and modelling techniques for real-world applications.

Time Series Analysis: Foundations

Examine the unique challenges of time series data and apply specialised tools and techniques using Pandas, Python, and NumPy to analyse and model data that changes over time.

Hackathon

Work collaboratively in teams on a project to apply newly acquired skills in real-world contexts.

Maths for Data Analysis

Explore essential mathematical concepts including probabilities, statistical significance, and linear algebra to build a strong foundation for understanding AI and Data Science principles.

Introduction to Machine Learning

Understand fundamental machine learning concepts and tools to effectively apply various models and techniques in practical scenarios.

Databases and SQL

Learn to use SQL to efficiently store, query, and retrieve both structured and unstructured data, enabling effective interaction with databases.

Web Scraping, Text-Mining, JSON and APIs

Explore web scraping, textmining, JSON, and API techniques to retrieve and process structured and unstructured data from various web-based sources.

Elective e-Learning Modules:

Supervised Learning

This intermediate module is designed to gain familiarity with an array of discriminative and generative supervised learning models as well as sophisticated techniques to evaluate model suitability and improve model performance.

Unsupervised Learning

This intermediate module covers a wide range of unsupervised learning models and techniques to reveal latent structure within your data and covers topics including KMeans, hierarchical clustering, DBSCAN, PCA and t-SNE.

Advanced Maths for Data Science

This intermediate level module is designed to build more advanced understanding of key mathematical concepts including probability, statistics, linear algebra, calculus and optimisation that underpin much of the AI and Data Science domain.

Eligibility

Intermediate to advanced users of spreadsheets in need of more efficient and powerful tools for working with data on a regular basis, who meet the following criteria:

Suitability of role

Proficient using spreadsheets and other IT software
Currently working with lots of data in large spreadsheets
Can identify how they will apply data analytics in their role to create business impact
Comfortable with algebra

Eligibility for funding

No prior Data or Computer Science degree or related experience.
Employed in England and resident in the UK or EEA for the last 3 years.
Employees working at least 30 hours a week (part-time employees can be considered for a minimum cohort size)
Can commit to the minimum 6 hours a week off the job learning requirement for the duration of the programme (14 months of training)

What makes the programme special

We deliver all of our programmes online, helping our clients offer flexible and inclusive programmes open to all of their staff. EDUKATE.AI, our online learning platform, gives learners a sandbox environment to practice their skills, providing them with immediate feedback on industry-simulated assignments. We believe that the gold standard for online delivery is to offer a mix of experiential learning, coaching, technical mentorship and peer support.

Python from Day One

Python is a powerful programming language that is widely used for data analysis. By teaching Python as a core component of our program, learners gain valuable skills that will position them for success in their careers.

Instant Feedback for Accelerated Learning

Our program benefits from the support of EDUKATE.AI, which provides instant feedback on coding work. This unique feature accelerates learning outcomes by allowing learners to see where they need to improve and make corrections in real time.

Real-World Practice for Accelerated Impact

EDUKATE.AI provides a sandbox environment where learners can practice new skills on real datasets. This accelerates the impact that learners can make in their workplace, allowing them to immediately apply what they've learned.

Personalized Learner Support

We provide each learner with a dedicated Data Mentor and Learner Success Coach to support them on their technical and personal development. This personalized support structure helps learners to succeed and overcome obstacles they encounter.

Flexible Fully Online Learning

Our program is fully online, providing maximum flexibility for learners and employers alike. This means that learners can access their content from anywhere, with no set up or installation of EDUKATE.AI required.

Expert Curriculum

Our comprehensive curriculum develops the skills for success in data analytics. As well as core skills such as Python, Pandas and data visualisation, the curriculum introduces learners to machine learning and includes electives in supervised and unsupervised learning.

Community

Joining our program means becoming part of a thriving community of thousands of data professionals. Learners have the opportunity to tap into this rich network of peers and alumni and benefit from the expertise and experience of others in the field.

FAQs

What delivery options do you offer?

We tailor our delivery to your workforce needs. This ranges from from independent, immersive elearning supported by EDUKATE.AI through to tailored bootcamps, to our structured apprenticeship programmes. The Level 4 Data Analyst Apprenticeship is available to learners based in England.

Are you able to tailor the programme to the organisation and sector?

Yes. We work with our clients to contextualise our programmes to their organisation and sectors they operate in. We do this through tailored hackathons, bespoke assignments and guest lectures from industry experts. We also work with a range of partners to create bespoke programmes for sector, such as health and journalism.

What is an apprenticeship?

Apprenticeships are a long-term training commitment which seek to support people entering the workforce and upskill existing UK-based employees within an organisation, enabling employers to foster a workforce consisting of highly-skilled and highly-engaged talent.

The Cambridge Spark Data Analyst Apprenticeship runs 14 months plus a 3-month end-point assessment and includes a minimum of 6 hours per week off-the-job training, enabling a blended approach between theory and practical-learning.

What is the Apprenticeship Levy?

The UK government introduced the Apprenticeship Levy scheme in April 2017 as a way to drive investment in strengthening the country’s skills base.

All organisations with annual staff costs of over £3m have to pay 0.5% of their salary bill into a ring-fenced apprenticeship levy pot. The money is collected monthly via PAYE and can only be used for training on approved apprenticeship schemes (such as the Level 4 Data Analyst Apprenticeship that we offer). Organisations must forfeit any levy funding left unspent for 24 months or more.

What if my organisation doesn't pay into the UK Apprenticeship Levy?

An organisation that doesn't pay into the levy can still qualify for government-funded apprenticeships for their staff. In fact, the UK government will sponsor 95% of the apprenticeship programme, leaving the organisation to invest the remaining 5%, provided that learners meet other eligibility criteria.

What does "off-the-job training" mean?

Off-the-job training is defined as learning undertaken outside of the day-to-day work duties and during the apprentice’s normal working hours.

Our off-the-job training is delivered on a flexible basis and can be carried out at the apprentice’s place of work or home.
The 6 hours per week, minimum, off-the-job training provides learners with the time to focus and develop the required skills, knowledge and behaviours to complete the programme.

How much do managers need to be involved?

Managers will need to ensure apprentices achieve their planned off-the-job training hours and work on their project portfolio.

We also encourage managers to have regular one-to-one meetings with apprentices to catch up on how they are progressing and to join the apprentice and their coach for 30 minutes every 3-4 months for a general catch up about the programme.

What is the Apprenticeship Levy?

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Data Analyst Apprenticeship (Level 4)

One data apprentice can create real business impact

Deliver on your data analytics strategy

The Curriculum

Core Modules

Elective e-Learning Modules:

Eligibility

Suitability of role

Eligibility for funding

What makes the programme special

Python from Day One

Instant Feedback for Accelerated Learning

Real-World Practice for Accelerated Impact

Personalized Learner Support

Flexible Fully Online Learning

Expert Curriculum

Community

A real-world learning experience

Enquire now

FAQs

Who's benefitted from our data apprenticeships

Case study

Case study

Case study

Case study