Degree apprenticeship

Data Science Degree Apprenticeship BSc (Hons)

An innovative degree in data science. Created in partnership with sector professionals.

Could this be the future's most important subject? Data Science graduates at York St John will have a thorough understanding of the intersection of computer science, statistics, mathematical modelling and communication.

  • Location – London campus
  • Duration – 3.5 years full-time
  • School – Psychological & Social Sciences

Course overview

You'll be well-rounded multi-disciplinary workers and communicators, interfacing with computer scientists, statisticians, clients, mathematical modellers, software engineers, communication professionals and organisational managers.

You'll study the collection of methods, tools and knowledge used to collect, analyse and interpret data and to tell the story behind the numbers. Face the future with  an breadth of career opportunities and specialist knowledge in understanding data and models, their scope and limitations, and the ability to design, question and communicate these to a wide range of audiences. You will learn cutting-edge Bayesian model selection and evaluation techniques, and mathematical and computational techniques for working with big data through databases, efficient algorithms, complex systems, machine learning and artificial intelligence.

You will have the intellectual space to focus on your studies whilst being able to apply what you have learned immediately in real-work contexts. You will learn with and from peer groups in similar situations and from individuals with different areas of specialisation. The format is blended, with face-to-face and online delivery as well as work-based learning. Your skills will allow you to make novel and unique contributions to your team and employer, and build a solid foundation for a broad variety of career paths.

Find out more about data science and the role of data scientists.

Course structure

Level 1

Foundations: Level 4 develops your understanding of the core data science areas of probability, statistics & data analysis, computer programming and communication. Modules in algebra, analysis and statistics will bridge the gap between school and university mathematics and underpin later advanced topics in data analysis, statistics and artificial intelligence. You will be taught the principles of Programming that will underpin all modules and which begins your training in Computer Science. You will gain valuable skills in creative problem solving and science communication in an interdisciplinary setting, learning and applying knowledge in mixed groups. This interdisciplinary exposure will teach you to see problems from different disciplinary perspectives and to communicate your insights to specialists outside your field. This provides essential preparation for your future position as an interface connecting multiple disciplines.

  • Programming
  • Linear Algebra
  • Communication
  • Practice in Interdisciplinary Problem Solving
  • Analysis & Optimisation
  • Probability, Statistics & Data Analysis

In terms of the block-teaching delivery in the first year, you will be learning about Programming, Linear Algebra, Practice in Interdisciplinary Problem Solving, Analysis & Optimisation, and Probability, Statistics & Data Analysis, whilst the Communication module will be taught in second year. This is due to the integrated nature of the degree apprenticeship and the integrated end-point assessment.

Level 2

Applications: Level 5 builds upon the multidisciplinary foundations in computer science, mathematics and communication laid at level 4. You will develop your ability to mathematically model and simulate diverse phenomena and systems in the world around you, both analytically and via computer simulations. Your computational skills will be extensively developed towards advanced programming and data handling techniques, using databases and object-oriented programming. You will get the opportunity to integrate different data science topics, tools and techniques in the context of the work-based project to investigate a real work data science project within your company, which also helps prepare you for the end-point assessment. This substantial individual research project allows you to accentuate your skills portfolio and develop your interests in different directions. This project is an extended piece of research and writing that shows your individuality, independence, creativity and communication skills.

  • Modelling & Numerical Analysis
  • Databases
  • Geometry & Groups
  • Object-oriented Programming
  • Graphs, Networks & Systems
  • Work-based Project

In terms of annual delivery pattern, in the second year you will study Communication, Databases, Modelling & Numerical Analysis, Geometry & Groups, and Object-oriented Programming.

Level 3

New directions: Level 6 gets you to an advanced level of mathematical and computational sophistication and specialisation, with a portfolio of skills. The first half of level 6 consists of advanced data science topics such as artificial intelligence, data visualisation and big data applications. The other half of level 6 consists of the end-point assessment. This in turn consists of a knowledge test, a report and a professional discussion. These address the knowledge, skills and behaviours (KSBs) set out in the occupational standard. You will continuously build an evidence-base for these via ePortfolios and reflections throughout your programme. The conclusion of the end-point assessment constitutes the completion of the academic BSc as well as the apprenticeship.

  • Advanced Data Applications
  • Data Visualisation
  • Artificial Intelligence
  • End-point Assessment

 In terms of the yearly delivery pattern, in the third year you will do the Graphs, Networks & Systems, Advanced Data Applications, Data Visualisation and Artificial Intelligence modules, as well as a work-based project. After these modules in third year you will have reached the end-point assessment gateway, which starts a 6-month window to perform the EPA in, which consists of a knowledge test, a project report and a professional discussion, which all draw on the knowledge you have gained in the course and on the job, and your progress towards the KSBs, which you will document in ePortfolios.

Teaching and Assessment

This programme is blended between on-the-job learning, online activities and face-to-face contact. Face-to-face contact concentrates on applying knowledge in new contexts that resemble the real-work setup in a collaborative and creative way. You will constantly blend your knowledge and skills to solve concrete problems. The assessments reflect this and are often based on analysing, solving and communicating a question, including writing your own software and data visualisations.

The forms of assessment are varied, and include written work for specialist and non-specialist audiences, written and practical exams, project reports and different communication formats such as videos, blogs, articles, briefs, social media content, posters etc.

Career outcomes

You will be employed already because your employer effectively sponsors your degree (see vacancy link above). Your talent will be systematically developed on this programme to grow into the role of a data scientist; to learn standard knowledge, skills and behaviours of the trade, and eventually to bring novel ideas, tools and techniques into your company, upskilling your team and finding novel solutions to your employer's projects.

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