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Course Description

This course builds on prior knowledge of Digital Twin systems and software platforms by introducing the processes, tools, and methodologies for integrating reality-captured data and foundational content into operational Digital Twins. Learners will explore techniques for acquiring spatial, visual, and sensor-based data through existing and emerging methods, including photogrammetry, lidar scanning, IoT sensor networks, and third-party data services.

The curriculum emphasizes the importance of data versioning, asset management, and content validation in complex, evolving Digital Twin environments. Learners will apply industry-standard version control systems to manage iterative updates to both geometry and data streams, ensuring reliability, traceability, and reproducibility.

Additionally, the course introduces the concept of the digital thread—the continuous, contextual data record that connects real-world operations with their virtual counterparts—highlighting its role in decision-making, predictive analysis, and lifecycle management. Through applied exercises, learners will integrate live or simulated data into a working twin environment, manage changes to foundational content, and structure data pipelines that support traceable, scalable digital systems.

This course is intended for learners seeking practical expertise in content integration, data governance, and operational continuity within Digital Twin workflows. This course is critical for helping learners understand the “plumbing” of digital twins—how data moves, evolves, and remains traceable. 

Course Outcomes:

  • Compare and contrast appropriate methods for capturing real-world assets for digital twin environments.
  • Integrate raw scanned stat into the digital twin environment while understanding scalability and reliability
  • Interact with two version control archetypes to understand source-of truth in the most common topologies
  • Analyze the role of the digital thread to track the inter-connection of a complex multi-software solution to help determine the complexity of change management.

This course includes a sandbox enviroment that allows learners to gain hands-on experience using Digital Twin software.

Applies Towards the Following Certificates

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Section Title
Digital Twin Data Sources & Reality Capture
Type
Professional Development Online Course
Dates
Jun 22, 2026 to Jul 20, 2026
Instruction Method
Course Fee(s)
Registration Fee non-credit $995.00

English Proficiency Requirements

Information on English Proficiency Requirements are located here.

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