Course on Simulating Urban Scenarios with AI
Online course of 300 hours in AI-based urban scenario simulation: 6 modules covering urban systems modelling, simulation data, artificial intelligence techniques, applied urban scenarios and responsible AI in public decisions, with an assigned technical tutor.
Course on Simulating Urban Scenarios with AI — studying from Australia
Australia's infrastructure pipeline is substantial, covering roads, rail, ports, water and urban development across major cities such as Sydney, Melbourne, Brisbane and Perth. Rail engineering is especially active, with projects including Sydney Metro and Melbourne Metro. Smart city initiatives draw on sensors, data platforms and digital twins to improve transport, utilities and public services. Employers include state transport authorities, engineering consultancies such as Aurecon and WSP, and major contractors. Engineers work on design, asset management, construction oversight and sustainability.
Fees for Australia: A$712 (AUD), with instalments and employer sponsorship available.
Relevant bodies in Australia
Typical roles
Questions from Australia
Does a SEIUM qualification meet Australian civil engineering registration requirements?
No. Civil engineers in Australia typically need an Engineers Australia accredited degree to pursue Chartered status, and state and territory rail and infrastructure regulators set their own requirements. SEIUM's private qualifications are not accredited by these bodies, so employers or regulators decide how much weight they carry.
Which Australian employers hire in civil, rail and smart cities?
Australia has public infrastructure agencies, rail operators, engineering consultancies and councils working on urban and smart city projects. Employers usually prioritise accredited qualifications, licensing and project experience. Ask potential employers whether a private online qualification would be considered alongside your experience.
Is the course workable alongside work, and what does it cost?
The courses are 100% online and taught in English, so you can study from anywhere in Australia without a student visa. Specialist courses take 300 hours, diplomas 800 and master's 1,900, so plan your time accordingly. Fees are payable in instalments, employer sponsorship may be possible, and you will have an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand the main paradigms for modelling urban systems.
Prepare data and synthetic populations for simulation.
Apply AI techniques such as surrogate models and reinforcement learning.
Simulate urban scenarios for mobility, climate, energy and growth.
Assess the uncertainty and fairness of results.
Apply the EU AI Act and the ISO/IEC risk management standards.
Develop an AI-based urban scenario simulation project.
Who it's for
- Urban modellers.
- Urban data scientists.
- Transport planners.
- Public-sector AI consultants.
- Urban science researchers.
- Territorial scenario analysts.
- Engineering or science graduates looking to move into local government.
What you'll work with
- Regulation (EU) 2024/1689 (Artificial Intelligence Act) (EU rules on artificial intelligence)
- ISO/IEC 42001 (AI management systems)
- ISO/IEC 23894 (AI risk management guidance)
- ISO/IEC 22989 (AI concepts and terminology)
- Regulation (EU) 2016/679 (GDPR) (EU General Data Protection Regulation)
- ISO/IEC 30173 (digital twin concepts and terminology)
- OGC CityGML 3.0 (3D city model data standard)
- ISO 37101 (management system for sustainable development in communities)
- MATSim
- SUMO
- Python with PyTorch
- UrbanSim
- NetLogo
6 modules
1.1The city as a dynamic system1.2Land-use and transport models1.3Agent-based models1.4Cellular automata and urban growth1.5System dynamics1.6Spatial interaction models1.7Temporal and spatial scales1.8Model calibration and validation1.9The role of AI in urban simulation1.10Case study: review of an existing LUTI model
2.1Census and municipal register data2.2Mobility data and household surveys2.3Synthetic population generation2.4Cadastral and building data2.5Satellite imagery and remote sensing2.6Climate data and IPCC scenarios2.7Integration into digital twins2.8Quality and bias in training data2.9Data protection in microsimulation2.10Lab: generating a synthetic population
3.1Supervised learning for urban prediction3.2Convolutional neural networks on urban imagery3.3Graph neural networks on road networks3.4Surrogate models for costly simulations3.5Reinforcement learning for urban control3.6Generative models for urban design3.7Language models as planning assistants3.8Model explainability3.9Uncertainty quantification3.10Workshop: surrogate model of a traffic simulation
4.1Mobility scenarios and urban road charging4.2Urban growth and housing4.3Heat islands and renaturalisation4.4Flooding and sustainable drainage4.5Energy demand and decarbonisation4.6Evacuation and emergencies4.7Impact of new infrastructure4.8Tourism and urban pressure4.9Equity and distribution of impacts4.10Practical exercise: comparing traffic removal scenarios
5.1The EU Artificial Intelligence Act5.2High-risk AI systems in the public sector5.3Risk management under ISO/IEC 238945.4AI management systems with ISO/IEC 420015.5Algorithmic bias and fairness5.6Transparency and communication of results5.7Citizen participation in scenario evaluation5.8Model and version governance5.9Limits of prediction in social systems5.10Case study: algorithmic impact assessment of a simulator
6.1Formulating the planning question6.2Choosing the modelling approach6.3Data preparation6.4Developing the simulation model6.5Incorporating AI techniques6.6Defining and running scenarios6.7Analysis of results and uncertainty6.8Ethical and risk assessment6.9Report and presentation6.10Final project: final review with the tutor
How you'll learn
The course is taught 100% online on the SEIUM campus, with downloadable materials, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it fits around your job.
Each module combines theory, guided reading of the original standards and applied exercises. You work with MATSim, SUMO, Python with PyTorch, UrbanSim and NetLogo, in free, academic or evaluation versions. Exercises are based on real procedures: simulating traffic restriction scenarios, generating a synthetic population for microsimulation and carrying out an algorithmic impact assessment of an urban model. Assessment is continuous by module, plus the final capstone project.
Standards covered: Regulation (EU) 2024/1689 (Artificial Intelligence Act), ISO/IEC 42001, ISO/IEC 23894, ISO/IEC 22989, Regulation (EU) 2016/679 (GDPR), ISO/IEC 30173, OGC CityGML 3.0, ISO 37101.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer able to run the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours over 3 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with MATSim, SUMO, Python with PyTorch, UrbanSim and NetLogo, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute certificate, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
No prior qualification is required; you need a computer with an internet connection and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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