Contact us

Interested in joining our next programme?

Enrolment Deadline

20th January 2024

Join our programme

One data apprentice can create real business impact

Imapact icon (1)

£1.4m revenue

identified through data-driven insights

Imapact icon

£120,000 saved

by creating efficiencies

Imapact icon (2)

90% shorter project times

achieved through automations

Imapact icon (3)

5x faster ML model training

achieved through automations

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.

Hear from Jonathan Wagstaff, Group Head of Business Intelligence at Exertis

Exertis logo

Hear from Jonathan Wagstaff, Group Head of Business Intelligence at Exertis

Exertis logo
Jonathan Wagstaff
Data apprenticeships enable myself and my team to keep up-to-date with the latest.

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 on the job learning requirement for the duration of the programme (14 months of training)
Union (8) (1)

What makes our 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.
Pioneers

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.
Feedback

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.
Practice

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.
Curriculum

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.
Personalized

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.
Online

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

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.
Edukate logo

A real-world learning experience

EDUKATE.AI is our learning experience platform which delivers a seamless experience in one place, and accelerates learning and impact through real practice on real projects with immediate personalised feedback on code.
Read more
Kate dashboard

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

Understand and become familiar with Python syntax, structure and programming concepts.

Join, manipulate and summarise datasets using the Pandas library.

Learn how to construct compelling charts and visualisations to communicate data-driven insights to technical and non-technical audiences, using libraries such as Seaborn and Bokeh.

Gain familiarity with industry-standard tools for creating interactive visualisations and business intelligence capabilities.

Learn to identify practical applications and use cases for data science and artificial intelligence that deliver and create business value.

Learn how to use SQL languages to store, query and retrieve structured and unstructured data and interact with databases.

Read and write JSON data with Python and learn automated methods for retrieving structured and unstructured data from a range of web-based sources.

Reinforce and develop the technical knowledge, practical skills and data analyst behaviours with a halfway hackathon.

Learn the essential mathematical concepts that underpin much of the AI and data science domain, including probabilities, statistical significance and linear algebra.

Build familiarity with a wide range of essential concepts and tools required to unlock the use of different types of machine learning models and techniques.

Learn to analyse and model series data with Python, Pandas and Numpy.

Learn to identify big data-related opportunities within an organisation and to leverage the power of distributed computing to extract value and insight at scale.

Learn about key ethical, legal and regulatory issues relating to the use of data.
Load more

Elective e-Learning Modules:

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.

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.

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.
Load more

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 Science Apprenticeship runs 15 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.
FAQ section (1)

Enquire now

Fill out the following form and we’ll contact you within one business day to discuss and answer any questions you have about the programme. We look forward to speaking with you.

Who's benefitted from our data apprenticeships

Why we’re the education technology training partner of choice.
case-study-thumbnail

Building AI capability in media and broadcasting with AI apprenticeships

Read more
case-study-thumbnail

Data Analyst Apprentice identifies £30k of savings for GSK

Read more
case-study-thumbnail

Deep Learning and Natural Language Processing (NLP) Training for Deloitte

Read more
case-study-thumbnail

Case study: Developing Python Programming Skills Within the NHS

Read more
View all our case studies