Two-Day Package: From BIM to Digital Twins: Integrated Workflows for Data-Driven Construction

Develop your BIM capability across the full digital workflow lifecycle, from structured model creation through to data integration, automation and Digital Twin applications.

This practical two-day CPD programme equips built environment professionals with the knowledge and skills to move beyond traditional BIM modelling and develop AI-enhanced, data-driven workflows. Across two sessions, participants will explore how BIM information can support scheduling, costing, asset management, automation, data visualisation and informed decision-making throughout the built environment lifecycle.

The programme combines information-rich BIM modelling, AI-supported workflows, automation techniques and Digital Twin concepts to help professionals transform project data into actionable insights.

Course Description

This practical two-day CPD programme is designed for built environment professionals who want to develop integrated BIM workflows and understand how structured project information can support data-driven decision-making across the full asset lifecycle.

Participants will explore how Building Information Modelling (BIM) can be developed, connected and transformed to support project scheduling, cost management, lifecycle information, automation, data visualisation, AI-assisted analysis and Digital Twin development. Across two sessions, the programme demonstrates how information flows from BIM model creation through to data integration, analysis and operational decision-making.

The programme takes a workflow-based approach rather than focusing solely on individual software tools, helping participants understand how BIM information can be structured, extracted, automated and communicated to improve project delivery and connected asset management.

Participants will also explore practical applications of Artificial Intelligence (AI) tools such as ChatGPT, Microsoft Copilot and AI-assisted Dynamo workflows to support BIM information planning, automation processes, quality checking, data interpretation and reporting. The programme emphasises responsible AI use, including validation of outputs, protection of project data and the importance of professional judgement.

Course Content

The programme covers:

• BIM principles: geometry versus information

• Structured BIM modelling, including families, parameters and naming conventions

• Level of Information Need (LOD/LOI)

• Preparing BIM models for scheduling, costing and asset management

• BIM as a foundation for Digital Twin development

• 4D BIM: construction sequencing and project scheduling

• 5D BIM: cost integration and estimation workflows

• 6D BIM: sustainability and lifecycle considerations

• 7D BIM: asset information and facilities management data

• BIM automation and interoperability challenges

• Introduction to Dynamo visual programming for BIM automation

• AI-assisted Dynamo workflow planning, explanation and troubleshooting

• Data extraction, transformation and automation workflows

• Digital Twin concepts and connected data environments

• Data visualisation and decision-support workflows

• Responsible AI use within BIM and Digital Twin applications

Practical Activities

Participants will gain hands-on experience with:

• Creating structured BIM models in Revit

• Adding BIM parameters such as cost information and asset IDs

• Generating schedules and exporting BIM data

• Linking BIM models to construction schedules using Navisworks

• Developing Dynamo workflows for BIM automation

• Using AI tools such as ChatGPT and Microsoft Copilot to support BIM information planning, workflow development and troubleshooting

• Preparing BIM datasets for analysis

• Creating Power BI dashboards to communicate project and asset information

Delivery Details

Dates:
Session 1: Saturday 5 September 2026
Session 2: Saturday 12 September 2026

Duration: 14 hours total (7 hours per session, including breaks)
Delivery: In-person
Location: Oxford Brookes University, Gipsy Lane, Headington, Oxford, OX3 0BP

Application deadlines:
Session 1: Thursday 3 September 2026
Session 2: Thursday 10 September 2026