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29 October, 2020 - 20:59 By Tony Quested

Cambridge Spark leads UK tech talent revolution

Raoul-Gabriel Urma

Cambridge Spark, a leading provider of data science and AI apprenticeships, has inducted more than 100 professionals in its latest cohort to undertake apprenticeships in data science, artificial intelligence and machine learning.

The apprentices will be in the Level 4 (data analyst) and Level 7 (data science and machine learning engineer) programmes. 

The Level 4 apprentices will be learning the basics of coding using Python language, which is a vital gateway to a wider coding career. The Level 7 apprentices undertaking the data science and machine learning engineer programmes are the first apprentices to do so in the UK.

The demand for data science professionals has tripled over the last five years (+231 per cent) according to a report by The Royal Society. However, thousands of roles continue to go unfilled as organisations struggle to find the talent they need. 

Data analysts, data scientists and machine learning engineers are amongst those that are most sought after. Apprenticeships offer a well-defined route for upskilling people into this kind of novel technical role.

Cambridge Spark is also working with Anglia Ruskin University to deliver more than 80 degree apprentices. Combined with the 50 apprentices Cambridge Spark is already training, this brings the total number of learners on degree-level programmes to over 200. This makes Cambridge Spark larger than many computer science departments at top UK universities.

Raoul-Gabriel Urma, CEO and founder of Cambridge Spark said: “This year's cohort of more than 100 apprentices marks a major achievement for Cambridge Spark in our mission to provide accessible training to help people to develop data science and machine learning skills and pursue new careers.
 
“The apprenticeship programmes we offer are more relevant and vital than ever before as major changes to the workforce increase the number of people looking for avenues to reskill.

“Working with business we are able to provide apprentices with degree level education and practical skills, which is an increasingly attractive alternative to the traditional academic path.

“Apprenticeships aren’t just for school leavers. They are open to current as well as new employees, people of any age, and even those with previous qualifications. It is an affordable option for people wanting to pursue a career in data science or AI and is also helping to provision the high skills that are in high demand in businesses.

“Those on our Level 7 programme will be among the best trained data science and machine learning professionals in the UK, delivering huge value to the organisations they work for and the overall digital economy.”

Huw Davies, senior early careers portfolio manager at the BBC said added: “We have been working with Cambridge Spark and other organisations in the Trailblazer group on the development and design of the apprenticeships. 

“The apprenticeships for us serve a dual purpose and offer a professional entry-level pathway for graduates and as well as offering an authentic route for our existing staff who require an applied and practical knowledge and skills training in machine learning as it becomes a more important part of our organisation.

“The 18 month apprenticeship has allowed us to bridge a skills gap in our mid to senior engineering teams as the pace of change has been significant across the domain of data science, ML and AI. 

“As a public service organisation, we need to ensure that we are knowledgeable and lead on data science for our sector while working safely and securely.

“We are excited to be able to offer this scheme to new and existing staff and working in partnership with Cambridge Spark, employers and UK universities to develop a centre of excellence surrounding Data Science apprenticeships.”

•  Enrolment for Cambridge Spark’s latest courses on Level 4 and Level 7 courses that begin in March are now open. To enrol visit: https://cambridgespark.com/ai-apprenticeships-l7-academy

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