The Data Scientist Degree Apprenticeship is suitable for individuals who have an interest in collecting, organising and studying data to provide new business insight that explores and visualises complex problems within industrial contexts. The apprenticeship leads to a BSc (Hons) in Data Science.
Who is it for?
A degree apprenticeship enables individuals to earn whilst they learn, combining academic study at University with substantial training and development of transferable skills in the workplace. Employers have the opportunity to upskill existing employees, or recruit new talent in to a role relevant to the apprenticeship.
Why do the apprenticeship?
The apprenticeship provides individuals to apply newly learned industry-specific knowledge directly in to the workplace, whilst working towards a BSc (Hons) degree qualification.
What are the benefits?
A Data Scientist Apprenticeship will develop the combination of skills and knowledge required to recognise different types of data and design, to implement and optimise appropriate methods of analysis. Apprenticeships are sponsored by employers, so employees pay zero tuition fees. All this whilst gaining invaluable industry experience, and earning a full time wage.
NTU has a major commitment to develop degree apprenticeship courses. NTU's apprenticeships are suitable for both small and large employers, and can be tailored to meet employers' specific business needs. The School of Science and Technology has:
- industrial experience built up and maintained through our industrial links and our applied research activity;
- ultra-modern facilities, equipment and software. This includes the new Interdisciplinary STEM Teaching and Engagement Centre (ISTEC), which features state-of-the-art laboratories;
- Access to academic programs from Microsoft, Oracle, IBM, SAS, and major software available across all campus computers;
- Experience in delivering BSc courses in Software Engineering, Computer Science, Computer Science (Games Technology), Information Systems, Computing, Computer Systems (Networks), Computer Systems (Forensics & Security), Computer Systems Engineering;
- BSc courses that are accredited by the BCS, The Chartered Institute for IT, to Chartered Engineer (CEng) and IT Professional (CITP) status.
Learn more about the Level 6 Data Scientist apprenticeship standard.
This online module introduces you to the fundamental Mathematical topics on which data scientists rely. It ensures your mathematical knowledge is up to speed and you can understand, unpack and manipulate mathematical expressions.
Introduction to Programming
You’ll get an introduction to a programming language which will be relevant to software used in industry. Programming language will be combined with material on appropriate algorithms and program structure elements such as libraries.
Foundations of Data Science
Building on the Introduction to Programming module, you’ll be introduced to data science focusing on a range of applied data analysis techniques in order to convert information into knowledge.
Learn and build the key academic and professional skills needed for successful completion of the degree element of your apprenticeship.
Data Science Systems Analysis and Design
Get to grips with the fundamental principles of system analysis and design (SAD) and the key systems development methodologies, techniques and tools used when developing a computer-based system.
Understanding LSEP in Data Science
Building on the knowledge gained in the Academic Skills module you’ll develop an understanding of the Legal, Social, Ethical and Professional (LSEP) issues affecting data scientists, and how they relate to your workplace.
Advanced Systems Programming
Develop the skills and knowledge required to develop robust, secure and efficient quality software. Using software development tools you’ll learn to apply object-oriented design techniques to develop high quality software.
Understand how data can be used to make professional judgements using classic hypothesis testing and confidence intervals, sampling and bias, regression and multivariate analysis. You’ll also learn to interpret the results of other data scientists.
Project Management Methodologies
You’ll evaluate how projects are managed in the workplace and how to propose alternative methodologies and tools.
Machine Learning for Data Science
You’ll be introduced to a number of ‘machine learning’ techniques to process and discover patterns in data. Developing your core knowledge and skills you’ll apply machine learning methods to real-world data sets in a systematic way using industry standards such as, the CRoss-Industry Standard Process for Data Mining (CRISP-DM).
Information Security for Data Science
Develop an awareness of the regulations and responsibilities held by an organisation during the process of data capture and processing. You’ll explore concepts of information security and assurance and develop an awareness of data storage security issues and the strategies for mitigating risks.
Scalable Systems and Database Engineering
Explore the processes, techniques and technologies data scientists use to support the challenging workloads for data science. You’ll study a range of distributed database technologies that can support big data and data science.
Artificial Intelligence for Data Science
Study the theoretical foundations of Artificial Intelligence (AI), the main methods and techniques, and current areas of AI research and development. Through practical exercises you’ll develop your understanding of AI techniques and systems including Game AI, Chatbots, Natural Language Processing (NLP) and Computer Vision and Optimisation.
You’ll develop the skills necessary for planning, managing and conducting a Data Science project which meets the requirements of the Apprenticeship Standard.
Data Science Work-based Project
In your workplace you’ll complete a substantial business-related project. It will bring together all the skills learned in previous modules including identifying problems and data science solutions for your organisation. You’ll use real data to design, measure and test your hypothesis before presenting and implementing your findings.
Data Science in Practice (End Point Assessment)
Using a variety of methods, including an exam, report and presentation, you’ll demonstrate that you’ve met the key objectives of the Data Scientist Apprenticeship Standard.
How you’re taught
The apprenticeship is delivered via blended learning blocks of five weeks. Apprentices will study online one day per week for four weeks, then come onto campus for two days of teaching in week five. There are also scheduled online one-to-one sessions between apprentices and tutors in between teaching blocks.
Learn a new language
Alongside your study you also have the opportunity to learn a new language. The University Language Programme (ULP) is available to all students and gives you the option of learning a totally new language or improving the skills you already have.
How you’re assessed
You will be assessed in a number of ways, including:
- Portfolio of practical work
To achieve the End-Point Assessment (EPA) and meet the apprenticeship standard the following assessment methods will be used:
- Knowledge test, followed by
- Report (based on a work-based project) and
- Professional discussion (informed by a portfolio)
Formative assessment is what NTU call the opportunities you have to produce and get feedback on work that will help you to prepare to complete your summative formal assessment. There are specific named activities which you will be asked to complete and submit for summative feedback. Additionally, peer, class and individual feedback on your ongoing work is formative.
Careers and employability
You'll also have the opportunity to turn your ideas into a viable business with help from NTU Enterprise, NTU's purpose-built Centre for Entrepreneurship and Enterprise, a support centre to help students create, develop and grow their own businesses.
Campus and facilities
Our Interdisciplinary STEM Teaching and Engagement Centre (ISTeC) building is the result of a £5 million investment from the government and NTU in recognition of the importance of STEM teaching.
The building contains state-of-the-art laboratories for teaching, and this is where engineering practical and workshop sessions will initially be held.
“This investment will mean world-class teaching facilities to build tomorrow's skilled workforce.”
Vince Cable, former Secretary of State, Department for Business, Innovation and Skills
Individual employers will set the selection criteria but this is likely to include three A levels, including maths, science or IT. Some employers will accept other relevant qualifications, such as BTEC or relevant experience.
EU students are eligible, please contact the apprenticeship team for eligibility information.
Unfortunately this course is not available for international students.
How to apply
How to apply
Applications to this course can be made through our NTU Applicant Portal.
Candidates are not required to attend an interview for this course.
Applications for the part-time course can be submitted up until the start of the course in October. Places are subject to availability, therefore we would advise early application.
Information for your employer
We have lots of useful advice and guidance on our website to help you discuss your options with your employer.
Please read our notes on the University's commitment to delivering the educational services advertised.
Unfortunately this course is not available for EU or international students.