Join our upcoming webinar to explore our Digital and Technology Solutions Apprenticeship MSc and the next steps to becoming a Cranfield University student. Hear from the Course Director, learn more about the course structure and gain an insight into some of the modules and content that will be covered. Register now.
This part-time programme meets the requirements of the Level 7 Digital and Technology Solutions Specialist Apprenticeship Standard. Eligible organisation’s are able to use £21,000 of their Apprenticeship Levy to cover the MSc tuition fee.

We are now open for applications for our next cohort in October 2023

Our Digital and Technology Solutions Apprenticeship MSc programme is unique and innovative compared to other courses as it takes a systems view to offer awareness and hands-on knowledge to design and develop digital technologies and solutions (including AI/Machine learning, digital twins, AR/VR, data analytics, data management) across industries that rely on complex engineered products and services. We will blend technical and managerial skills to promote the creation, adoption, and evolution of digital technologies and solutions. We will also take an innovative approach to deliver the course with cutting edge blended learning methods.

The course will significantly improve the career prospects of students as they will be equipped with the skills to not only choose the right digital technologies and solutions across the life cycle of complex engineered assets, but also they will be capable to apply their knowledge to create solutions to significant challenges

The Digital and Technology Solutions MSc is a world-leading programme developed by Cranfield with close engagement with industry sectors such as defence, aerospace, rail, and wider manufacturing. Designed for industry professionals to fit around demanding careers, the course has been designed to develop the skills to lead change in business through digital technologies.

Overview

  • Start dateOctober
  • Duration24 months part-time
  • DeliveryTaught modules 80 credits, group project 40 credits, individual practical project 80 credits.
  • QualificationMSc
  • Study typeExecutive
  • CampusOnline and Cranfield campus

Who is it for?

This course is novel as it brings together technical and management skills in the digital theme. Our differentiator will be to take a systems perspective to design and develop digital technologies and solutions across manufacturing based industries. The unique selling point of the course is to move beyond raising awareness of digital technologies and processes, in to developing individuals to have the required capability and understanding to develop suitable solutions to key industrial problems.

For those who recognise the potential for a long and successful career utilizing digital technologies and solutions across the different phases of the life cycle for complex engineered assets. This course addresses the need for highly trained professionals that rely on digital technologies and solutions required to transform operations into a world-class business in all sectors of manufacturing and is suitable for:

  • Experienced professionals who are seeking or are required to take on senior leadership roles within manufacturing or related organisations.
  • Early and mid-career professionals who want a “real-world” education that they can apply directly to their workplace.
  • Second career professional seeking a change into manufacturing or digitally driven organisation.

Informed by industry

Our courses are designed to meet the training needs of industry and have a strong input from experts in their sector. Based on industrial engagement, the common feedback for the mode of delivery of the course was blended learning (roughly 10% on campus / 90% off campus). It was highlighted that in light of financial constraints there is a need to minimise travel needs and do block sessions. It was suggested that particularly Programming & Projects could be delivered remotely. We will also develop a model for face-to-face collaboration and networking to be hosted largely at Cranfield University – Bedford campus throughout the course that minimises the need to travel, but maximises the engagement among the participants. We also intend to arrange meet-ups at partner industrial sites as needed in the course.

Key information

The Digital and Technology Solutions Apprenticeship is structured to allow maximum benefit from learning with minimum time away from the working environment.

Benefits for businesses

  • Establish new mechanisms to justify new investments in digital technologies and solutions.
  • Seize the potential opportunities that digital technologies and solutions offer by developing the skills required to develop and apply innovative approaches within your organisation.
  • Enhance approaches for data collection, storage and analytics for better decisions.
  • Gain an appreciation of how simulation methods can be applied to enhance business enterprises.
  • Develop a wide understanding of artificial intelligence and machine learning based approaches which derives higher confidence in predictions.
  • understanding of how to develop leadership capabilities in themselves, and others, enabling them to meet your business challenges.
  • Candidates are encouraged to think strategically about digital technologies and solutions as enabling capability for delivering a competitive advantage to the business, and ensuring organisational functions and groups are motivated and aligned to meet objectives.

Benefits for individuals

  • Join a programme that provides new insights, knowledge and skills in digital technologies and solutions that can shape your future career and prepare you for future senior leader roles.
  • Develop your understanding of best practice in digital technologies and solutions in order to improve operational effectiveness.
  • Develop digital technology and solutions that enable the delivery of innovation and performance improvement.
  • Develop a strategic mindset for the execution of growth strategies and achievement of business objectives enabled by digital technologies and solutions.
  • Apply your newly acquired knowledge, skills and abilities immediately in your workplace.
  • Study with a cohort of talented professionals drawn from a range of industries and backgrounds, building your network and giving insights into international practice.
  • Become a member of our alumni network and join a network of 67,000+ across 169 countries.

How we teach you

The course is composed of three core parts:  

  1. Eight compulsory modules spread between months 1 and 16. 
  2. Group project between months 6 and 12. This comprises 4 to 6 people working on a project that is relevant and impactful, and typically relates to real industry jobs.
  3. Individual practical project (IPP – for apprentices) / individual research project (IRR – for non-apprentices). The student, in collaboration with the employer and the university will determine an individual project that is aligned to their day-to-day job and offers to make a significant impact on the business. This business-related project will run between months 14 and 24 and will be written up as a report between months 21 and 24. During months 20 and 21 time will be allocated to the gateway assessments (for apprentices) and presentation preparation (for non-apprenticeship students). Apprenticeship students will need to complete the End Point Assessment between months 21 and 24.

Apprenticeship students, throughout the whole course, will need to provide evidence for the Knowledge, Skills and Behaviours (KSBs). KSBs are mapped for each credit-bearing part of the course and students will need to reflect on their learning and demonstrate how they have been able to make an impact in their organisation according to this mapping. The End-Point Assessment (EPA) element will be assessed through the individual practical project report and the professional discussion. In the report, students will need to highlight how each KSB has been addressed. Similarly, in the professional discussion, the KSBs need to be evidenced through a portfolio of evidence. 

The apprenticeship students will quarterly have tripartite meetings with their apprenticeship tutor, and their company sponsor to discuss their progress against the KSBs, and will have the opportunity to reflect on their learning and the impact that they are making in the sponsor organisation. As the EPA organisation, Cranfield takes on the following responsibilities:

  1. Provide an apprenticeship tutor for each student to undertake the quarterly tripartite meetings throughout the course.
  2. Manage the gateway assessment for each student.
  3. Manage the EPA delivery with at least two independent assessors that have not been involved in the course.
  4. Facilitate lectures and projects that will enable students to fulfil the required KSBs for each specialism.

The induction module will be delivered face-to-face, but there will be opportunities to join online. All modules will be delivered based on project based learning (PBL), which is integral to the delivery of the course, in order to provide challenges, which have been co-designed with industry, to provide a central focus to each taught module. Taught modules 1 and 8 (Introduction to Digital Engineering and Digital integration and System Testing) will be delivered wholly face-to-face. In module 1, we will introduce PBL and promote networking across the cohort. Module 8 will deliver an integrated digital solution, which will require very close engagement on physical and digital assets.

The PBL approach will provide students with the opportunity to investigate, explore, and collaborate in the process of solving problems through case studies. Accordingly, each module will be systematically structured around a significant industrial challenge (or a set of challenges) that is relevant to the particular module.Industrial challenges have been developed through a series of workshops with over 20 organisations to capture common cross-organisational challenges that are impactful commercially and technically. In PBL, the interaction between the lecturer and students will be enabled by applying a range of methods, including case studies, experiments, storyboards, questionnaires developed by students to interact with experts, mindmaps, interactive graphs, AR/VR, simulation models, worked examples, and tutorials. Sessions will be based on group discussions, research and guidance provided by the module leader or lecturers. The guidance will be offered in various formats, including recorded videos to be viewed prior to or during the module, live presentations on particular points, supplementary content such as academic papers and industrial white papers or open discussions.

Modules 2 to 7 will be delivered through distance learning, with both live lectures/interaction through an online portal and recorded material (e.g. videos) that will be shared through the virtual learning environment (VLE).  

Students will work in groups to address the challenges set through PBL in each module. A series of live face-to-face /online and recorded guidance material, including technical lectures, will facilitate the students’ process of addressing the set challenges. The group activity within modules will not be graded, but it will serve as formative assessment. The feedback on this by lecturers and the module leader will help the students to prepare the assignment that forms the module level summative assessment. Across the modules, students will progressively work on the development of an integrated digital technology and solution for an industry-led challenge. This will not be graded and will be part of the formative assessment within the modules. The sequence of modules has purposefully been constructed in order to build the integrated solution in a modular manner. The individual project promotes on-the-job learning alongside independent self-study to solve an industrial challenge. focused on the digital technology and solution creation.These challenges will typically be strategic or operational in nature and will be value-driven, based on the impact that a digital technology or solution can make.   
 
Students will engage regularly (e.g. around every 3 months) with a course independent tutor who will have the role of facilitating implementation of new knowledge in the workplace and to clarify any on-going queries. For apprentices, the tutor will also provide guidance with the process of evidencing the required KSBs necessary for the gateway in month 20 of the programme. The tutor will also provide the opportunity to engage with the industrial line manager / sponsor to offer a path for effective organisational impact from the course. Students will also have up to two academic supervisors to guide with the research and direction of studies during their group and individual project components.

Awards on completion

On successful completion, the student will be awarded:

  • The Level 7 Digital and Technology Solutions Apprenticeship
  • MSc in Digital and Technology Solutions

Fees for MSc progression route

Our Digital and Technology Solutions Apprenticeship is an MSc-integrated programme spread over 24 months. In England, it is aligned to the L7 apprenticeship standard on Digital and Technology Solutions. This means that organisations that fulfil the conditions for the Apprenticeship Levy will have the tuition fees covered in full on this course. 

It is also possible register on the programme as an MSc student without going through the apprenticeship route.

We also offer the modules as short courses on this MSc course. 

 

Meet the Course Director

If you are unable to attend one of our University Open Days but would like to discuss the Digital Engineering and Solutions programme, please get in touch.

During your discussion you will have the opportunity to:

  • meet the Course Director
  • discover more about the course content
  • find out how you can use your company's Apprenticeship Levy towards this Cranfield MSc
  • learn about our manufacturing faculty

We would be happy to arrange a virtual discussion via MS Teams or Zoom.

I look forward to discussing Digital Engineering and Solutions and how it can benefit you and your business with you soon.

Professor John Erkoyuncu

Course details

The course aligns with the Master's Level Apprenticeship in Digital and Technology Solutions with the following targeted occupational streams: Data Analytics Specialist and Digital Business & Enterprise Systems Architecture Specialist. The course is delivered over 24 months. The course will compose of three core parts:

  • Eight modules (80 credits – 10 for each module),
  • Group project at 40 credits,
  • Individual practical project (80 credits).

The modules will typically be spread over 18 months. The group project will run between months 6 and 12, and the individual practical project will be completed between months14 and 24. Developing practical solutions is at the heart of each of these elements, where we will work closely with the industrial sponsors to make the course as impactful as possible for both the student and the organisation. Across the course we will co-design the assessments with the industrial sponsors in order to develop useful solutions. Furthermore, the assignments across the modules will be designed to complement each other and lead to the creation of a comprehensive demonstrator at the end of the modules. 

 

Course delivery

Taught modules 80 credits, group project 40 credits, individual practical project 80 credits.

Modules

For cohorts starting in November 2022:

  • Introduction to Digital Engineering
  • Digital Business & Enterprise Systems
  • Digital Twins
  • Integrated Data Management
  • Digital Business Analysis
  • Data analytics and Artificial Intelligence
  • Adaptive visualisation
  • Digital integration, System Test & Assurance

Modules

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.


Course modules

Compulsory modules
All the modules in the following list need to be taken as part of this course.

Introduction to Digital Engineering​​

Aim
    This module provides the skills to choose and justify new digital technologies and solutions by implementing appropriate requirements analysis, technology road-mapping and strategy development considering alternative targets such as return on investment and customer value.
Syllabus
    Introduction to digital engineering including digitalisation vs digitisation vs digital transformation 

    Introduction to requirements capture and systems engineering 

    Justifying Prevent, Safeguarding and British Values in the context of the digital technologies and solutions that will be considered for adoption  

    Building awareness and justification of digital technologies and solutions 

    Technology road-mapping to evaluate future potential technological developments  

    Return on Investment analysis in the context of digital technology and solutions 

    Developing a strategic plan for digital transformation and the future work environment considering the role of technology leadership, change management and continuous improvement.
Intended learning outcomes

On successful completion of this module you should be able to:

Justify appropriate methods for requirements capture for digital technology and solutions within the system of system context  

Appraise the opportunities that digital engineering offers by developing roadmaps for alternative digital technologies and solutions 

Critique and design methodologies to evaluate and prioritise digital technologies for alternative requirements including return on investment 

Critically evaluate human-machine collaboration in the face of automation and manual tasks in industrial settings 

Develop a strategic plan to seize the potential benefits of digital engineering via workplace transformations whilst considering a variety of factors such as ethics, human factors, IP, culture, sustainability, and value. 

Digital Business & Enterprise Systems

Aim
    The module aims to provide a system engineering based approach to identify the requirements and processes for the design of digital technologies. As part of this module, the adoption of technologies and solutions into businesses to support digital transformation will be identified, evaluated and established. 
Syllabus
    • Introduction to design thinking (lean/agile) for digital technologies adoption  
    • Fundamentals of process mapping, and business capability modelling 
    • Assessing project management methodologies & governance models on digital transformation 
    • Develop and build a Digital Business Ecosystem architecture to enable interoperability 
    • Evaluating the impact of technologies in the context of: 
      Paths and pathway for successful implementation 
      Social & cultural impact on digital disruption & transformation 
      Human factors  
Intended learning outcomes

On successful completion of this module you should be able to:

Construct systems engineering based process mapping methods to evaluate business requirements for digital transformation.  

Justify approaches for design thinking (e.g. lean / agile) in the context of digital transformation in enterprises. 

Assess digital architectures and technology roadmaps that enable digital transformation and communicate optimal delivery pathways. 

Construct a suitable digital architecture and the associated delivery roadmap(s) for strategic adoption and implementation of digital technologies. 

Critically evaluate the impact of organisational and human readiness and culture for digital transformation. 

Integrated Data Management

Aim
    This module will provide the skills to be able to build a system simulation architecture and associated model for agile decision making within an enterprise context. 
Syllabus
    Introduction to modelling including overview of simulation methods and techniques. 

    Simulation design and development 

    Root cause analysis and risk management for digital engineering 

    Business process analysis and outcomes prediction 

    Environmental sustainability analysis.
Intended learning outcomes

On successful completion of this module you should be able to:

Appraise different methods for business systems simulation design 

Justify the use of simulation models to address significant decisional needs in business management 

Compare and contrast the performance of alternative digital business processes through case studies 

Construct alternative decision-making models for business process optimisation through case studies 

 

Digital Twins

Aim
    This module focuses on providing the skills to design and develop federated digital twin systems that are integrated in terms of their data, models and visualisation. 
Syllabus
    Introduction to digital twins and demonstration of use cases 

    Introduce the key enabling technologies for digital twins -such as ontologies, AI, and IoT 

    Design detailed digital twin architectures including solutions for interoperability 

    Standards available to design and develop digital twins 

    Develop digital twin demonstrations considering the spectrum of data, model and visualisation interfaces 

    Demonstrate the added value that digital twins can offer 
Intended learning outcomes

On successful completion of this module you should be able to:

Appraise the contextual need for digital twins and design the digital twin architecture justified by suitable requirements and organisational benefits.  

Compare and contrast alternative digital twin architectures, which meet the functional and strategic requirements 

Justify efficient use of digital twins considering human needs in the context of  seamless data, model and visualisation interaction 

Construct suitable resilience methods that enable continuous use of digital twins 

Evaluate the added value generated from digital twins with a view to offer workplace transformations.

Integrated Data Management

Aim
    This module provides the skills to design and develop integrated data management approaches and systems to address data related challenges. This includes managing large volumes of data from disparate sources, identifying and resolving data quality issues, handling disparate data lacking integration and generating insights for agile decision making that are integrated in terms of their data, models and visualisation for agile decision making.
Syllabus
    • Introduction to software programming with a view to developing data management systems
    • Evaluate existing standards related to data management
    • Apply methods for data needs analysis
    • Establish mechanisms for enabling connectivity of data acquired from alternative sources – e.g. people, sensors, 5G, IoT
    • Develop data structures and approaches to data modelling using ontologies and reference architectures
Intended learning outcomes

On successful completion of this module you should be able to:

  • Assess the system requirements for the integration and accessibility of data to deliver value in complex systems
  • Critically evaluate existing approaches to acquire data from fixed and mobile sources
  • Appraise strategies and techniques to measure and optimise the quality of data
  • Construct efficient data structures enabled by ontologies and reference architectures to allow continuous and standardised data flow
  • Justify mechanisms for allowing connectivity of data to enable links to models and visualisation platforms

Data Analytics and Artificial Intelligence​

Aim
    This module will provide the processes to design and develop artificial intelligence (AI) based approaches to be trained for data analytics on a spectrum of data types (e.g. messy data, data gaps or big data), whilst also considering the ethical implications. 
Syllabus
    • Theory of data analytics, AI, ML, data mining, statistics and supervised learning, e.g., probability, decision trees, regression and classification.   
    • Experience of real-world AI/ML applications, in areas such as engineering, business, social media, medical data and financial data  
    • Evaluate alternative ethical considerations including human-machine collaboration that are related to the use of AI/ML.  
    • The opportunity to work on industry problems that can benefit from AI/ML approaches. 
Intended learning outcomes

On successful completion of this module you should be able to:

  • Compare and contrast data analytics methods including machine learning (ML) in terms of its current and future concepts, principles and theories. 
  • Construct ML concepts and methods to impart innovative problem-solving skills in a variety of data maturity scenarios. 
  • Evaluate value creation opportunities from ML, develop value propositions and revenue models for businesses and organisations 
  • Construct data analytics-based methods for real world problems with the changing nature of digital technology infrastructure and varying volume and quality of data; 
  • Appraise ethical responsibility considering human-machine collaboration in data analytics by reflecting on intelligent systems that benefit society. 

Adaptive visualisation

Aim
    This module aims to provide the ability to design and develop digital visualisation platforms that enable agile decision-making capability.
Syllabus
    Introduction to visualisation methods 

    Awareness of human machine interfaces and the associated challenges and solutions 

    Communication skills for effective illustration and collaboration on complex results 

    Design and develop dashboards, virtual and augmented reality demonstrators 
Intended learning outcomes

On successful completion of this module you should be able to:

Appraise different methods of visualisation for detailed data analysis  

Evaluate human-computer interaction methods and their relevance to visualisation 

Assess technical narrative and consolidated information for knowledge exchange and effective decision making  

Justify the use of dashboards, virtual and augmented reality for adaptive visualisation through case studies 

Digital integration, System Test & Assurance

Aim
    This module will provide the skills to be able to integrate a set of digital technologies and solutions for a wider application and offer the means to test the integrated solution for assurance purposes. 
Syllabus
    Introduction to system integration methods 

    Awareness of technical standards and the associated requirement and implementations 

    The processes for test case development and developing a test management plan 

    Understanding of safety and mission assurance and associated QA processes 

    Critical evaluation criteria and risk assessment strategies for digital engineering 
Intended learning outcomes

On successful completion of this module you should be able to:

Justify with sufficient evidence the efficient integration of a set of digital engineering technologies and solutions 

Appraise testing standards and qualify their relevance to quality assurance (QA) processes  

Compare, contrast and develop test management strategies for new digital technologies and solutions 

Critically evaluate safety and mission assurance for a digital engineering technology and solution 

Teaching team

You will be taught by a wide range of subject specialists here and from outside the University who draw on their research and industrial experience to provide stimulating and relevant input to your learning experience. Many of the lecturers have worked in industry themselves, some at Managing Director level, and have experience of leading the design, development and implementation of digital engineering and solutions. Guest lecturers include speakers from Rolls-Royce plc, BAE Systems, MoD and Siemens. Excellent staff to student ratios lead to focused discussion about real-world issues in implementing operations excellence. The Course Director and Admissions Tutor for this programme is John Erkoyuncu.



Your career

The Digital and Technology Solutions Apprenticeship will enable you to develop your knowledge, skills and abilities while applying what you learn directly in your workplace. The programme will support your career progression, preparing you to successfully carry out senior leadership roles in the future..

Apart from developing your technical skills, the course will support you to:

  • Develop digital engineering skills to make operational and strategic improvements in enterprises and projects,
  • Apply digital technologies and solutions to address challenges and introduce innovation,
  • Discover and develop your leadership and team-working style,
  • Develop and lead change and prepare the business to face future digital transformation.

Our Career services team offer: individual career consultations, speaker events, alumni networking, networking workshop, personal and executive career coaching, leadership assessment centre, and more practical skills-based workshops on writing CVs and cover letters, and interview skills.

How to apply

Next steps

If you would like to find out more general information about the course and your eligibility to attend the programme, please arrange a one-to-one discussion with the course director before you make a formal application.

Course director: John Erkoyuncu: j.a.erkoyuncu@cranfield.ac.uk

For employer related enquiries, fees and funding, and the expression of interest/application process, please contact our Apprenticeships Team: apprenticeships@cranfield.ac.uk

Employers: please complete our Expression of Interest form.

Prospective students: please ask your employer to submit an Expression of Interest form to indicate their willingness to sponsor you.

Applications for apprenticeship routes have to come via the Expression of Interest form. Apprenticeship applications received via the application button on the non-apprenticeship pages will not be processed. 

Expression of Interest form