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Course structure

The course is planned over 4 weeks with 6 hours of active learning using best-practice examples (remote lectures delivered in real time and recorded for catch-up) and a strategic discussion forum with the cohort. Lecture sessions run once a week.

By participating in the sessions and successfully completing the course, you will receive a ̽»¨¾«Ñ¡ Certificate of Attendance and a digital badge.

This course is the second part of a series, the first course focuses more on Digital Twin Strategy and Transformation and introduces digital twins, explores their applications and use cases, guides participants in developing strategies to drive efficiency, productivity and long-term value.

Note: The Digital Twin Strategy and Transformation and Digital Twin Implementation courses run in succession, so you can register for both if you wish.

What you will learn

By the end of the course, you will be introduced to:

• Development of a unified framework for designing scalable digital twin solutions,
• Architectural approaches and methodologies for digital twin development,
• Enabling interoperability, federation and effective data management across complex systems,
• Semantic modelling using ontologies and knowledge graphs,
• Applying AI, machine learning, and analytics to enhance decision-making,
• Designing automated feedback mechanisms supporting continuous improvement.

Timetable

The programme runs over four weeks through live online sessions, and collaborative discussions with peers working on similar implementation challenges. Each week focuses on a critical capability required to deliver operational digital twins and all sessions are recorded and made available to participants.

 

Week 1: Foundations: Digital Twin Design Architectures and Methodologies

Explore alternative design approaches for successful digital twin implementation.

Topics include:

• Introduction to unified digital twin architectures and design methodologies,
• Reference architectures and standard system components,
• Development frameworks for scalable solutions,
• Linking physical and digital systems through structured design approaches.

Week 2: Ontologies, Knowledge Graphs and Semantic Modelling

Understand how semantic technologies enable interoperability and shared understanding across digital twin ecosystems.

Topics include:

• Ontologies and semantic data modelling,
• Knowledge graphs for system integration,
• Data structuring and contextualisation,
• Supporting federation through shared data models.

Week 3: Interoperability and Federated Digital Twin

Dive into interoperability approaches that enable collaboration across platforms and organisations.

Topics include:

• Interoperability challenges in digital twin ecosystems,
• Standards and frameworks supporting integration,
• Introduction to Asset Administration Shell (AAS) concepts,
• Designing systems that support federation and automated feedback loops for continuous improvement and long-term value creation.

Week 4: Artificial Intelligence in Digital Twins

Examine how AI and analytics transform digital twins into intelligent and adaptive systems.

Topics include:

• Role of AI and machine learning within digital twins,
• Predictive and prescriptive analytics in the context of digital twins,
• Data pipelines supporting AI deployment,
• Enabling smarter operational decision-making.

Learning Pathway

This course forms part of a two-stage digital twin learning journey:

1. Digital Twin Strategy and Transformation: understanding value, strategy, and organisational adoption

2. Digital Twin Implementation: designing and delivering operational digital twin systems

Participants may take both courses consecutively.

Who should attend

This course is designed for professionals involved in the design, delivery, or technical leadership of digital twin initiatives. It is particularly suited to participants with foundational knowledge of digital twins who want to deepen their implementation capabilities.

Typical participants include:

• Solution architects and technical leads,
• Systems and software engineers,
• Data engineers and platform specialists,
• AI and analytics professionals,
• Digital innovation and R&D teams,
• Consultants supporting digital twin deployment,

The course complements the Digital Twin Strategy and Transformation programme and represents the next step for those moving from planning to execution.

Partnerships

This course is delivered with the as part of the Gemini Skills Training Programme, bringing together expertise from industry, academia, and the public sector to advance digital twin capability across the UK ecosystem.