Summary of the Multiverse Data & AI academy
We have partnered with Multiverse to give current staff members the opportunity to complete a range of Data and AI qualifications funded by the Apprenticeship Levy. See our webpage to find out more about Staff Apprenticeships.
Deadlines for applications
There will be 2 application forms to fill out, the first for your details and the second for your project idea. Line management approval for your project will be required.
The application deadline is Wednesday 30 April 2025
Please attend the information sessions below or email workforce development for further details on how to apply.
Please register your interest to attend the information sessions to find out more.
Information Sessions
Information sessions are taking place on the following dates and times:
Data Academy
- Tuesday 1 April 12pm (1 hour)
- Wednesday 9 April 3pm (1 hour)
AI Academy
- Thursday 3 April 2pm (1 hour)
- Thursday 10 April 11am (1 hour)
Case Study: University of Cambridge
Here is an example of how a data apprentice was able to make real impact by applying their learning at the University of Cambridge:
The International Student Office at the University of Cambridge must balance compliance with sponsor licenses while delivering high-quality services to thousands of international students. Historically, a reliance on manual data entry and outdated processes led to inefficiencies and uncertainty in decision-making, leaving the team overstretched during peak periods.
The learner joined the Data and Insights for Business Decisions programme designed to address these challenges. Her project focused on cleaning and visualising data on international student withdrawals. By applying new skills and tools such as PowerBI, she streamlined processes and improved the teams' ability to analyse historical data.
Her work created a sustainable, self-serve data culture that empowered her team to make confident, data-driven decisions. The insights gained from her analysis allowed the office to identify trends in student withdrawals and implement effective interventions, directly enhancing the student experience. By automating manual tasks, her project resulted in significant time savings, allowing the team to focus on higher-value activities during peak periods. Additionally, her skill-sharing initiatives within the team have reduced reliance on spreadsheets, improving overall efficiency and reducing operational costs associated with manual errors.