Key information
- Duration:
- 3.5 years plus End Point Assessment (EPA)
- Start date:
- September 2025
This apprenticeship prepares you for a career at the cutting edge of business analytics and computer science.
You’ll develop quantitative and analytical skills, as well as coding and programming capabilities required by modern business analysts in a variety of sectors. You’ll have access to our Bloomberg Financial Markets Lab, located in the University of Sussex Business School and high-specification computing facilities within our School of Engineering and Informatics.
Teaching methods will include online study as well as learning on campus at Sussex. As an apprentice, you’ll be registered as a University of Sussex student and have access to our:
This course is mapped to the IfATE-standard Digital and Technology Solutions Professional degree apprenticeship. As an apprentice, you’ll spend 20% of your paid working hours in protected learning time, ensuring minimal disruption.
This course is currently subject to validation, in line with our procedures for assuring the quality of our degrees. This means that some course detail and content may change as we develop this new course. The validation process will be finished before your course starts.
How to apply
Employer
If you want to offer an apprenticeship for an existing employee or a new recruit, contact us at apprenticeships@sussex.ac.uk
Apprentice
We work with employers to identify the right employees to sign up to our apprenticeship programmes. If this in an area that interests you and you are already in employment, ask your employer to contact us at apprenticeships@sussex.ac.uk
We understand that deciding where and what to study is a very important decision. We’ll make all reasonable efforts to provide you with the courses, services and facilities described in this prospectus. However, if we need to make material changes, for example due to government, professional body or regulatory requirements, or unanticipated staff changes, we’ll let you know as soon as possible.