Postgraduate (2 years part-time, work-based, degree apprenticeship)
This course is delivered through blended learning: work-based study, online through a combination of our Learning Management System, Canvas and Cambridge Spark’s K.A.T.E.® platform, plus immersive teaching weeks and an online hackaton-style bootcamp.
Develop and apply specialist data science tools and techniques to process large, complex datasets in order to extract and derive valuable insights to inform decision making within your organisation. Gain an MSc Digital and Technology Solutions (Data Analytics) degree while you work, with fees funded by your employer and the Government.
Data science, in particular coupled with artificial intelligence, promises to provide the tools for enhanced technologies, business models and decision making across a large number of fields, from industrial automation, manufacturing, transport, banking and cyber security to health and social care.
Through working on real-world datasets and industry-simulated projects, you will learn the skills and knowledge required to apply the latest advanced data science tools and techniques such as data engineering and deep learning.
The MSc Digital and Technology Solutions (Data Analytics) will be delivered in partnership with Cambridge Spark, a leading provider of continuous professional development training for developers and data scientists.
This cutting-edge course is taught as a blend of immersive teaching weeks, online study and a hackathon-style bootcamp which simulate real-world environments.
20% of your learning will be classed as ‘off the job’, which means that you'll be learning during normal working hours either in your place of work or outside – but not part of your normal working duties.
As well as learning while you earn, the benefits of studying this course include:
My MSc apprenticeship course leader Dr Vicinanza has re-ignited my interest in Time Series and R. I can see myself using this for a long time in my career.
There is a recognised significant skills gap in data science based systems specialists in the industry, nationally and internationally. This is despite data scientist roles growing over 650% since 2012, with machine learning engineers, data scientists, and big data engineers ranking among the top emerging jobs*.
Employers have highlighted the importance of data science and its potential to revolutionise a number of industries, from social sciences, physics and engineering to market analysis and banking, while creating significant employment opportunities for data analysts, machine learning specialists and data specialists.
Typical job roles include big data analyst, data and insight analyst, data science specialist, data management specialist and analytics lead.
*U.S. Bureau of Labor Statistics.
Assessment will be via a variety of methods including time constrained assessments, coursework assignments and project.
The dissertation project and module case studies assess your ability to analyse situations, identify key issues, select, synthesise and apply techniques and skills from different modules and to be able to evaluate the appropriateness of their solutions when compared to industrial practice.
The dissertation artefact will be based on a real-world scenario related to or actually part of an actual piece of project work in a company.
End Point Assessment (EPA)
This apprenticeship features an ‘integrated’ End Point Assessment. It gives you the opportunity to demonstrate that you have attained the skills, knowledge and behaviours set out on the standard.
There are two parts to the end-point assessment:
The Faculty of Science & Engineering is one of the largest of the four faculties at Anglia Ruskin University. Whether you choose to study with us full-time or part-time, on campus or at a distance, there’s an option whatever your level – from a foundation degree, BSc, MSc, PhD or professional doctorate.
Whichever course you pick, you’ll gain the theory and practical skills needed to progress with confidence. Join us and you could find yourself learning in the very latest laboratories or on field trips or work placements with well-known and respected companies. You may even have the opportunity to study abroad.
Everything we do in the faculty has a singular purpose: to provide a world-class environment to create, share and advance knowledge in science, technology and engineering fields. This is key to all of our futures.
You will need:
ARU’s standard procedures for admission with credit will apply if you wish to be considered for Accredited Prior Learning (APL) and Accredited Prior Experiential Learning (APEL) for entry into Year 2 or later of the course.
We will also consider applicants with non-standard qualifications provided you have a significant amount of relevant experience, are well-supported by your employer, and demonstrate the ability to manage university-level study.
ESFA approved Level 2 Maths and English qualifications are mandatory.
Course offers can only be made if approved Level 2 certificates are provided prior to the start of the course.
For further details about which qualifications meet Level 2 requirements download this document from: the gov.uk website
Read this institution's report