Master’s degree1,500 h · Online · 11 modules

Master's in Digital Twins for Ships and Ports

This master's programme gives you command of the creation, management and analysis of digital twins applied to ships and terminals. You will work with sensor data, simulation models and interfaces with operational systems, with case studies showing the benefits in port and onboard operations.

Duration1,500 h

ModeOnline

Start1 December

Modules11

Programme diagnosis

Prior knowledge check

These are the skills this programme gives you. Tick the ones you already master and we will tell you which part of the syllabus is for you.

Your diagnosis

6of 6 to cover

You are starting from scratch in this subject. The programme is designed precisely for that.

About the programme

What is the Master's in Digital Twins for Ships and Ports?

This master's programme prepares you to lead the digital transformation of the maritime sector. You will learn to create, manage and analyse digital twins, virtual replicas that improve the design, operation and maintenance of vessels and port infrastructure. It covers 3D modelling, IoT sensors, data analytics and artificial intelligence, applied to real cases.

Its strengths are advanced simulation, predicting how ships and ports will behave under different operating conditions; supply chain optimisation, improving logistics efficiency and reducing operating costs; predictive maintenance, anticipating failures and extending asset life; innovative design, testing configurations and materials virtually; and an integrated vision that brings ship and port together in a single digital ecosystem.

Programme typeMaster’s degree

ModeOnline

Duration1,500 hours

Modules11

Start1 December

Programme highlights

Technology mastery: create and manage digital twins of ships and ports with current tools.
Advanced simulation: run predictive simulations to optimise operations, reduce costs and improve safety.
Real practical cases: work on projects applied to the maritime and port sector.
Career boost: acquire highly sought-after skills to lead digital transformation.
Application in industry: put your knowledge into practice in companies in the sector and contribute to their innovation.

Syllabus

Syllabus of the Master's in Digital Twins for Ships and Ports

11 modules. Select a module to see its content.

Module 1

Fundamentals of Digital Twins and Maritime Industry 4.0

1.1. Definition, types and architecture of Digital Twins in the maritime and port sector
1.2. Milestones of digital transformation in ports and shipping companies: Smart Ports and Connected Ships
1.3. Digital Twin life cycle: design, construction, operation and decommissioning
1.4. Interoperability and industry standards: OpenMETA, ISO 23247 and DNV/ABS specifications
1.5. Subsea, surface and port IoT infrastructure: vibration, inclination, pressure and flow sensors
1.6. Real-time data transmission networks: industrial 5G, LoRaWAN, LEO satellite and MQTT/OPC UA protocols
1.7. Cloud and Edge Computing for processing maritime big data
1.8. Cybersecurity in maritime OT/IT environments: protecting digital twins against intrusions
1.9. IMO (International Maritime Organization) regulations and the impact of digitalisation on decarbonisation
1.10. Cost-benefit analysis and return on investment (ROI) in the implementation of digital twins

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 2

3D Modelling, CAD/CAM/CAE and Laser Scanning for Maritime Twins

2.1. Point clouds and geometric capture: LiDAR laser scanning and photogrammetry of ships and quays
2.2. Building Information Modelling (BIM) applied to port infrastructure (ISO 19650)
2.3. High-fidelity 3D naval CAD modelling: hulls, superstructures, machinery and shaft lines
2.4. Conversion of static models into interactive dynamic models for real-time environments
2.5. Real-time graphics engines for hyper-realistic visualisation: Unreal Engine, Unity and Omniverse
2.6. Parametric modelling of STS and RTG cranes, automated terminals and mooring fittings
2.7. Integration of GIS (Geographic Information Systems) data and 3D bathymetry into the port model
2.8. 3D mesh optimisation and multi-level rendering (LOD – Level of Detail) for smooth execution
2.9. Augmented (AR), Mixed (MR) and Virtual Reality (VR) for technical inspection and immersive operations
2.10. Management of digital assets and libraries of standardised marine components

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 3

Ship Digital Twin: Structure, Hydrodynamics and Seakeeping Behaviour

3.1. Digital hydrodynamic model: Computational Fluid Dynamics (CFD) for calculating resistance
3.2. Seakeeping simulation: roll, pitch, yaw and response to irregular waves
3.3. Real-time structural monitoring: strain gauges, material fatigue and hull bending (hogging/sagging)
3.4. Digital twin of the propulsion system: main engines, turbochargers, shaft lines and propellers
3.5. Simulation of auxiliary systems: boilers, separators, ballast systems and water treatment
3.6. Digital management of stability and trim: integration of ballast tanks and real-time weight calculation
3.7. Digital twin of alternative-energy ships: methanol, ammonia, hydrogen and wind-assisted propulsion
3.8. Assessment of hull wear from corrosion and biofouling using predictive models
3.9. Experimental vs. digital validation: correlation between towing tank tests and CFD
3.10. Certification and approval of ship digital twins by Classification Societies (Lloyd's, DNV, ABS)

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 4

Digital Twin of Navigation Systems, Routes and Autonomous Ships (MASS)

4.1. Integration of AIS, GPS/GNSS, radar, ARPA and ECDIS data into the navigation digital twin
4.2. Simulation of optimised ocean routes (weather routing) based on real-time waves, wind and currents
4.3. Digital twins for Maritime Autonomous Surface Ships (MASS): IMO degrees of autonomy
4.4. Collision avoidance algorithms (COLREG) applied to autonomous ships in simulated environments
4.5. Digital modelling and testing of high-precision berthing and unberthing manoeuvres
4.6. Simulation of critical failures at sea (Failure Mode and Effects Analysis – FMEA) in autonomous ships
4.7. Virtual HIL (Hardware-in-the-Loop) testing for the validation of autopilots and DP (Dynamic Positioning) systems
4.8. Digital replication of ship-to-ship and ship-to-channel hydrodynamic interaction (bank/bottom effect)
4.9. Shore-based Remote Operation Centres (ROC) supported by digital twins of ships under way
4.10. Predictive analysis of environmental impact: dynamic calculation of the CII (Carbon Intensity Indicator)

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 5

Digital Twin of Port Infrastructure and Terminal Operations

5.1. Digital modelling of maritime works: breakwaters, quays, jetties and anchorage areas
5.2. Simulation of wave agitation within the harbour basin and resonance/seiche using numerical models
5.3. Digital twin of cargo-handling equipment: STS and RTG cranes, reach stackers and AGVs
5.4. Digital replication of the container terminal: yard management, cargo segregation and optimal moves
5.5. Digital twins for liquid bulk, dry bulk and roll-on/roll-off (Ro-Ro) terminals
5.6. Simulation of landside access: bottlenecks at gates, rail and truck traffic
5.7. Real-time sensor monitoring of fenders, bollards and mooring line tensions
5.8. Planning and optimisation of berth allocation (Berth Allocation Problem) through simulation
5.9. Digital replication of the port energy network: smart grids, photovoltaics and onshore power supply to ships (OPS)
5.10. Assessment of climate change impact: simulation of sea-level rise and extreme weather events

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 6

Data Analytics, Machine Learning and Prediction in Maritime Twins

6.1. Massive streaming data ingestion pipelines from ships and port sensors (Apache Kafka/Spark)
6.2. Cleaning of marine telematics data: GNSS noise filtering, imputation of missing data and anomaly detection
6.3. Machine Learning algorithms for predictive maintenance of marine and port machinery
6.4. Estimation of the Remaining Useful Life (RUL) of cranes, hulls and propulsion systems
6.5. Predictive models for ship waiting times (dwell time) and port congestion forecasting
6.6. Reinforcement Learning for automatic scheduling of crane operations
6.7. Physics-Informed Neural Networks (PINNs) applied to fluid mechanics and marine structures
6.8. Algorithms for detecting spills and pollution in port waters combining computer vision and the digital twin
6.9. MLOps for continuous updating of predictive models in the Digital Twin
6.10. Building operational dashboards and predictive KPIs for management decision-making

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 7

Process Simulation, Logistics and Port Supply Chain

7.1. Discrete Event Simulation (DES) applied to port logistics (AnyLogic, FlexSim, Siemens Plant Simulation)
7.2. Integration of the port Digital Twin with TOS (Terminal Operating System) and PCS (Port Community System)
7.3. Simulation of the intermodal supply chain: port–rail–road and connectivity with micro-hubs
7.4. Digital replication of the port cold chain (reefer containers): temperature traceability and disruptions
7.5. Optimisation of positioning and relocation of empty containers (housekeeping optimisation)
7.6. Modelling of queues and maritime traffic flows in access channels and pilotage areas
7.7. Simulation of conventional and clean-fuel (LNG, hydrogen) bunkering operations
7.8. Integration of port storage logistics with ERP systems and customs portals
7.9. Stress and resilience testing of the supply chain against global disruptions (strikes, accidents, pandemics)
7.10. Assessment of terminal energy performance and carbon footprint using simulation scenarios

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 8

Digital Twin for Safety, Rescue and Emergency Management

8.1. Digital simulation of port emergencies: vessel fires, chemical leaks and explosions
8.2. Modelling of pollutant dispersion, toxic clouds and oil spills (Oil Spill Modelling)
8.3. Digital twins for maritime search and rescue (SAR) management: simulation of survivor drift
8.4. Simulation of passenger evacuation on mega cruise ships and in passenger terminals
8.5. Monitoring of extreme structural conditions during storms at offshore installations and ports
8.6. Rapid response protocols guided by digital twins in collision or grounding accidents
8.7. Integration of AI video surveillance systems (CCTV) with the 3D port model for access and risk control
8.8. Training of port emergency personnel through immersive VR/AR simulations
8.9. Risk analysis and critical vulnerability points (HAZOP) on the Digital Twin
8.10. Maritime business continuity plans based on disaster recovery simulations

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 9

Digital Twin Platforms, Software Architecture and Integration

9.1. Leading Digital Twin platforms: Microsoft Azure Digital Twins, AWS IoT TwinMaker and Bentley iTwin
9.2. Development of microservices and RESTful/GraphQL APIs for data connection between marine systems and the cloud
9.3. Integration of real-time physics engines for simulating mooring, loads and impacts at the quay
9.4. Creation of Knowledge Graphs to represent complex ship–port–cargo relationships
9.5. Open data models and domain-specific ontologies for the maritime and port sector
9.6. Development of UX/UI user interfaces for state-of-the-art port command and control centres
9.7. Integration with blockchain technologies to audit the integrity of twin data
9.8. Deployment of Digital Twins in hybrid environments (on board the ship / in the port cloud)
9.9. Low-latency data synchronisation strategies between the ship at sea and the port ashore
9.10. Maintenance, software updates and change management in port IT projects

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 10

Implementation, Cybersecurity and Return on Investment of Digital Twins

10.1. Implementation roadmap
10.2. Platform and vendor selection
10.3. Cybersecurity of the digital twin
10.4. Data governance
10.5. Standardisation and interoperability
10.6. Organisational change management
10.7. User training
10.8. Value indicators
10.9. Return on investment
10.10. Implementation case study

At this stage

136 hestimated workload

11 wkweeks at your pace

Module 11

Master's Final Project: Implementation of a Maritime/Port Digital Twin

11.1. Selection of the real case study: Ship Digital Twin (propulsion, structure or routes) or Port Digital Twin (terminal, water or access)
11.2. Definition of the system architecture: data capture, Edge/Cloud processing and visualisation layers
11.3. 3D geometric survey or integration of the CAD/BIM model of the infrastructure or ship
11.4. Configuration of the IoT layer: simulation or ingestion of real-time telematics data
11.5. Development of dynamic simulation models (hydrodynamic, logistic, structural or predictive)
11.6. Implementation of predictive analytics or artificial intelligence algorithms for optimisation
11.7. Integration into the Digital Twin platform and development of the operational control dashboard
11.8. Validation of the Digital Twin: accuracy tests, response times and usability analysis
11.9. Preparation of the technical report, architecture manual and economic-operational feasibility plan
11.10. Public presentation, real-time functional demonstration and oral defence of the project before a panel of experts

At this stage

136 hestimated workload

11 wkweeks at your pace

Plan your pace

Duration and format of the Master's in Digital Twins for Ships and Ports

It is 1,500 hours. Tell us how many you can study each week and we will tell you when you will really finish.

Hours per week

4 h30 h

With 12 h per week

months to finish

125 weeks

weeks in total

This is the pace at which most students finish. It fits well with the instalment plan.

Faculty

Academic leadership and faculty

The Navalis teaching team: working professionals who teach and supervise the programmes.

Dra. Marina AlcoverAcademic Director and Head of Quality Assurance

Ing. Diego CifuentesSenior Lecturer in Naval Welding and Non-Destructive Testing; Head of QA/QC for Welded Joints

Cap. Javier Abaroa (MCA)Senior Lecturer in Ship Handling, Electronic Navigation (ECDIS/Radar/ARPA) and GMDSS; STCW Compliance and Bridge Resource Management Coordinator

Dr. Pau FerrerSenior Lecturer in Naval Architecture and Simulation; Director of the Hydrodynamics and CFD Laboratory

Dra. Nuria LlobregatSenior Lecturer in Marine Meteorology, SAR and Operational Safety; Navigation Risk Management Coordinator

Ing. Javier BañulsSenior Lecturer in Electrical Engineering, Automation and ETO Engineering; Electronic Integration and Engine Alarms Coordinator

Ing. Sofía MarquinaSenior Lecturer in Materials, Composites and Corrosion Protection; Coordinator of the Advanced Paints and Coatings Line

Ing. Tomás RieraSenior Lecturer in Propulsion, Alternative Energy and Hybrid Systems; Energy Performance and Vibration Coordinator

Objectives

Objectives of the Master's in Digital Twins for Ships and Ports

01Optimise predictive maintenance.

02Simulate maritime emergency scenarios.

03Assess the energy efficiency of maritime operations.

04Implement smart port management systems.

05Improve strategic decision-making.

06Develop predictive models of maritime behaviour.

Careers

Career opportunities after the Master's in Digital Twins for Ships and Ports

01Digital twin developercreating and maintaining virtual replicas of ships and ports.

02Maritime simulation engineerdesigning and running simulations to improve operations and safety.

03Maritime digital transformation consultantadvising companies on implementing digital twins.

043D modelling and visualisation specialistbuilding accurate models and interactive visualisations.

05Maritime data analystextracting valuable insight from the data generated by twins.

06Innovation project managerleading the development and implementation of new technologies.

07Maritime technology researcherdeveloping new applications for digital twins.

08Port operations optimisation expertimproving the efficiency and safety of ports.

09Predictive maintenance specialistpredicting failures and optimising ship maintenance.

Frequently asked questions

Questions about the Master's in Digital Twins for Ships and Ports

Digital representations of physical maritime assets, such as ships and ports, that use real-time data and simulations to optimise design, construction, operation and maintenance.

Yes. The programme includes ECDIS/Radar-ARPA/BRM with port, ocean, fog, heavy-weather and SAR scenarios.

Online with live sessions; hybrid option for simulator placements/internships through partnership agreements.

It covers both aspects: the creation of digital replicas (digital twins) and the management/operation of ships and ports using these replicas.

Functional SMCP is recommended. We provide support materials for standard phraseology.

Yes, with a related qualification or experience in maritime/port operations. The admission interview will confirm your suitability.

Optional (3–6 months) through Companies & Partnerships and the Alumni Network.

Simulator exercises (rubrics), passage plans, SOPs, checklists, micro-tests and an applied master's thesis.

Related programmes

More programmes in Innovation and startups

View the whole area →

Master’s degree · 1,500 hMaster's in Machine Learning for Maritime SecurityA$4,460 · View programme →Short course · 300 hCourse in Generative AI for Shipping Companies and PortsA$960 · View programme →Master’s degree · 1,500 hMaster's in 3D Modelling and Virtual Reality for Naval EngineeringA$3,940 · View programme →

Online admission

Admission process

No waiting for a call back. If your documents are in order, you can enrol in the same session.

Entry requirements

Academic or professional profile: degree in Naval Engineering, Computer Science, Industrial Engineering, Naval Architecture, Marine Sciences or a related field, or accredited professional experience in the maritime and port sector.
Language skills: technical English is recommended for working with digital twin software and documentation.
Prior knowledge: notions of 3D modelling, programming, simulation or BIM are valued.
Documentation: up-to-date CV, copy of your degree, identity document or passport, and a letter of motivation.
Technical requirements (online): a computer capable of running modelling and simulation software, a high-speed connection and, preferably, a dedicated graphics card. Admission is provisional until the committee validates the documentation.

01
Application
Your details, background and documents.
02
Instant review
We check that everything is complete and in order.
03
Enrolment
Choose full payment or instalments and reserve your place.

Start my applicationFrom A$2,752 deposit

Admission is provisional until the committee validates the documents provided. If you do not meet the requirements, the full amount is refunded.

Any questions?

Ask us before you enrol

Leave your details and admissions will write to you to answer any questions. If you are already sure, you can apply and pay in the same session.

Enrol now