Course Introduction
Digital Engineering for Infrastructure Project Managers Course explores how integrated digital technologies, data environments, engineering models, automation, analytics, and connected information systems are transforming the planning and delivery of infrastructure projects. Infrastructure programs increasingly involve complex assets, multiple engineering disciplines, geographically distributed teams, extensive stakeholder networks, and large volumes of technical information. Digital engineering provides project managers with structured methods for connecting these elements to improve coordination, visibility, predictability, and delivery performance.
The course examines how digital engineering extends beyond conventional engineering design and BIM by creating integrated information flows across the infrastructure project lifecycle. Participants explore how digital models, geospatial information, engineering data, project controls, asset information, sensors, reality capture, and digital platforms can work together to support better project decisions. The focus is on helping project managers understand the management implications of digital engineering without requiring them to become specialist software users or engineering modelers.
Participants will examine applications across roads, railways, bridges, airports, ports, utilities, water systems, energy infrastructure, tunnels, public facilities, and other complex infrastructure programs. Digital engineering can support feasibility analysis, requirements management, design coordination, constructability, scheduling, cost management, procurement, risk management, quality assurance, construction monitoring, commissioning, and asset handover. The course demonstrates how project managers can use integrated digital information to identify interfaces, manage dependencies, anticipate problems, and coordinate multidisciplinary delivery more effectively.
A major focus is placed on integrating digital engineering with project management processes and controls. Participants explore connections between engineering models, geographic information systems, BIM, schedules, cost systems, work breakdown structures, risk registers, change management, document environments, and performance dashboards. They learn how to establish information requirements, manage digital deliverables, coordinate engineering disciplines, monitor model maturity, and ensure that technical information remains aligned with project objectives, contractual requirements, construction activities, and management decisions.
The course also addresses the organizational, governance, and implementation challenges associated with digital engineering. Infrastructure projects can encounter fragmented technology environments, inconsistent data standards, interoperability limitations, unclear information responsibilities, cybersecurity risks, inadequate digital skills, contractual uncertainty, and resistance to new ways of working. Participants therefore examine practical approaches for establishing digital engineering governance, information assurance, common data environments, collaboration protocols, quality controls, security measures, and change management practices that enable digital engineering to deliver measurable project value.
Emerging developments receive particular attention, including digital twins, artificial intelligence, generative engineering, automated design checking, reality capture, drones, computer vision, IoT-enabled infrastructure, cloud engineering environments, predictive analytics, and AI-assisted project controls. Participants explore how these technologies are converging to create increasingly intelligent infrastructure delivery ecosystems. By the end of the course, project managers will be better prepared to lead digitally enabled infrastructure projects, manage engineering information strategically, coordinate technical stakeholders, and use digital intelligence to improve delivery certainty, project performance, and lifecycle outcomes.
Duration
5 days
Who Should Attend
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Infrastructure Project Managers responsible for planning, coordinating, and delivering complex engineering projects
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Program Managers overseeing major infrastructure programs involving multiple engineering disciplines and delivery organizations
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Project Controls Managers integrating engineering information with schedule, cost, risk, and performance management
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Engineering Managers responsible for multidisciplinary technical coordination and engineering deliverables
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Design Managers coordinating infrastructure design development, reviews, interfaces, and technical information
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BIM Managers and Digital Engineering Managers implementing model-based infrastructure delivery practices
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Construction Managers managing the transition from engineering information to physical infrastructure delivery
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Project Planners seeking to integrate engineering models with schedules, sequencing, and progress management
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Quantity Surveyors and Cost Managers working with engineering quantities, models, estimates, and cost information
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Contract Managers managing digital engineering requirements, technical deliverables, and information obligations
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Asset Managers involved in infrastructure handover, asset information, and lifecycle management
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GIS and Geospatial Professionals supporting infrastructure planning, engineering, and project delivery
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Quality Managers responsible for engineering information quality, verification, assurance, and compliance
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Digital Transformation Professionals implementing digital engineering strategies across infrastructure organizations
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PMO Professionals seeking to establish consistent digital engineering governance and project delivery standards
Course Objectives
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Understand the principles, processes, technologies, and strategic value of digital engineering for modern infrastructure project planning and delivery.
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Explain how digital engineering connects engineering models, BIM, GIS, project controls, asset information, and project management processes across the lifecycle.
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Identify opportunities to apply digital engineering to infrastructure planning, design coordination, construction, commissioning, handover, and operational readiness.
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Develop practical approaches for managing digital engineering requirements, deliverables, information standards, model maturity, and multidisciplinary technical coordination.
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Integrate engineering information with schedules, costs, risks, procurement, quality, change management, progress monitoring, and infrastructure project controls.
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Evaluate digital engineering risks involving interoperability, information quality, cybersecurity, data ownership, contractual responsibilities, and technology dependencies.
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Establish effective governance frameworks for digital engineering covering responsibilities, information assurance, collaboration, approvals, security, and decision-making.
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Explore how digital twins, artificial intelligence, reality capture, drones, IoT, computer vision, and analytics can enhance infrastructure project delivery.
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Improve stakeholder collaboration by establishing structured digital workflows that connect owners, engineers, contractors, consultants, suppliers, and project management teams.
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Develop a practical digital engineering strategy that improves project visibility, coordination, predictability, delivery performance, and long-term infrastructure information value.
Comprehensive Course Outline
Module 1: Foundations of Digital Engineering for Infrastructure Projects
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Understanding digital engineering principles, terminology, capabilities, and their growing role in infrastructure project management and delivery.
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Examining the evolution from traditional engineering documentation toward integrated, model-based, data-driven infrastructure project environments.
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Identifying digital engineering applications across feasibility, planning, design, procurement, construction, commissioning, and asset management.
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Defining the project manager’s role in digital engineering strategy, governance, stakeholder coordination, information management, and delivery assurance.
Module 2: Digital Engineering Strategy, Requirements, and Information Management
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Establishing digital engineering objectives and information requirements based on project scope, delivery methods, stakeholder needs, and lifecycle decisions.
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Developing digital execution strategies covering models, data, standards, workflows, responsibilities, deliverables, reviews, approvals, and information exchanges.
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Aligning digital engineering requirements with project execution plans, BIM strategies, contracts, procurement approaches, and organizational information standards.
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Managing digital information throughout its lifecycle while maintaining consistency, traceability, accessibility, security, and appropriate levels of information maturity.
Module 3: BIM, GIS, Geospatial Data, and Infrastructure Engineering Models
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Understanding how BIM, GIS, CAD, engineering models, surveying information, and geospatial datasets contribute to integrated infrastructure project delivery.
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Coordinating multidisciplinary models covering roads, bridges, utilities, structures, drainage, rail, buildings, terrain, and other infrastructure components.
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Managing spatial reference systems, coordinate requirements, model alignment, data exchange, classification, metadata, and information consistency.
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Applying integrated digital models to improve spatial coordination, engineering decisions, constructability assessment, stakeholder communication, and project planning.
Module 4: Digital Engineering for Infrastructure Planning and Design Coordination
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Using digital engineering to support feasibility studies, options analysis, requirements definition, design development, and infrastructure planning decisions.
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Applying model-based coordination to identify design interfaces, constructability concerns, technical conflicts, dependencies, and multidisciplinary engineering issues.
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Integrating engineering information with project requirements, scope structures, design review processes, risk registers, and change management workflows.
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Establishing digital design review and approval processes that improve technical collaboration, decision traceability, and alignment with project objectives.
Module 5: Digital Engineering for Scheduling, Cost, and Project Controls
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Connecting engineering models and digital information with work breakdown structures, schedules, activities, milestones, and infrastructure construction sequencing.
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Applying 4D and 5D approaches to integrate engineering information with schedule visualization, quantities, estimates, budgets, and cost forecasting.
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Using digital engineering data to strengthen progress measurement, schedule analysis, change impact assessment, cost control, and project performance reporting.
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Developing integrated project control environments that combine technical, schedule, cost, risk, quality, and progress information for management decisions.
Module 6: Digital Engineering for Construction, Quality, and Risk Management
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Applying digital engineering information to construction planning, site coordination, work packaging, temporary works, logistics, installation, and field decision-making.
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Integrating models with inspection processes, quality requirements, technical submissions, verification records, nonconformance management, and corrective actions.
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Using digital information to identify engineering risks, interface constraints, constructability problems, design gaps, and potential delivery disruptions.
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Establishing workflows that connect technical issues with project risk registers, action tracking, change control, approvals, and construction management processes.
Module 7: Digital Engineering for Infrastructure Data, Collaboration, and Delivery Governance
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Establishing common data environments and collaborative digital platforms for managing engineering models, drawings, specifications, reports, and project records.
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Defining responsibilities among owners, designers, consultants, contractors, suppliers, engineers, project managers, and digital engineering teams.
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Managing information quality, version control, model approvals, technical reviews, digital deliverables, and controlled information exchanges across project organizations.
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Addressing contractual, intellectual property, information ownership, cybersecurity, interoperability, and liability considerations within digital engineering environments.
Module 8: Digital Engineering for Construction Monitoring and Asset Handover
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Integrating digital engineering with drones, laser scanning, reality capture, computer vision, mobile technologies, and field data to monitor infrastructure construction.
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Comparing planned engineering information with actual site conditions to identify deviations, incomplete work, changes, and potential quality or schedule concerns.
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Developing digital handover strategies that connect engineering models and asset information with commissioning, operations, maintenance, and lifecycle requirements.
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Establishing information assurance processes that verify digital deliverables for completeness, accuracy, usability, consistency, and long-term asset management value.
Module 9: Digital Engineering Governance, Cybersecurity, and Implementation Challenges
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Establishing governance frameworks covering digital engineering standards, responsibilities, information assurance, approvals, security, compliance, and performance measurement.
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Managing interoperability challenges between engineering applications, BIM platforms, GIS systems, project controls, enterprise systems, and cloud-based collaboration environments.
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Assessing cybersecurity, data protection, technology dependency, information leakage, unauthorized access, and other risks affecting infrastructure digital ecosystems.
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Developing digital engineering implementation roadmaps addressing technology selection, capability development, organizational adoption, training, standards, and continuous improvement.
Module 10: Intelligent Digital Engineering, Digital Twins, and Emerging Technologies
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Exploring digital twins that connect engineering models, IoT sensors, operational data, project controls, asset information, and real-world infrastructure conditions.
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Examining AI-assisted engineering analysis, automated model checking, generative design, intelligent information extraction, and predictive project performance applications.
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Evaluating emerging technologies including computer vision, autonomous surveying, drones, edge computing, robotics, connected infrastructure, and AI engineering agents.
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Developing strategic approaches for creating intelligent infrastructure delivery ecosystems that provide continuous digital insight from project conception through asset operation.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
