Diploma in Demand Models and Control Strategies
Online postgraduate diploma of 800 hours in demand models and control strategies: 8 modules covering mobility demand, discrete choice models, activity-based models, short-term demand forecasting, traffic control strategies, demand management and operational integration with DATEX II and GTFS, with an assigned technical tutor.
Diploma in Demand Models and Control Strategies — studying from the United States
Data science, artificial intelligence and simulation are central to American industry, with major concentrations in the San Francisco Bay Area, Seattle, New York and Boston. Engineering organizations increasingly rely on machine learning, digital twins and high-performance computing to accelerate design, testing and operations. Employers range from large technology companies to aerospace, automotive and energy firms that apply analytics to complex systems. Demand is strong for engineers who combine domain knowledge with modeling, statistics and software skills.
Fees for the United States: US$1,220 (US Dollars), with instalments and employer sponsorship available.
Relevant bodies in the United States
Typical roles
Questions from the United States
Which US bodies relate to data science, AI and simulation engineering?
There is no single licensing body for data science or AI in the US. Relevant professional organizations include the IEEE Computer Society, the Association for Computing Machinery (ACM), and the Society for Industrial and Applied Mathematics (SIAM). Federal guidance such as the NIST AI Risk Management Framework shapes practice. SEIUM's qualifications are private and not accredited by a national body, so recognition is decided by employers.
How do US employers in data and AI regard private online postgraduate qualifications?
US tech firms, financial institutions and research labs generally hire on the basis of portfolios, technical interviews, relevant experience and sometimes advanced degrees. A private online qualification can show structured study, but it is not a standard hiring requirement and each employer weighs it differently. Public projects, code repositories and measurable results tend to matter most.
Is it realistic to study data and AI from the US around a full-time job?
Yes, the programmes are fully online and taught in English, so you can study from home without a student visa. The workload is large: about 1,900 hours for a master's, 800 hours for a postgraduate diploma, and 300 hours for a specialist course. An assigned technical tutor supports you. Fees may be paid in instalments, and employer sponsorship is sometimes available, which you should confirm with your employer.
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
Analyse mobility demand from surveys and big data.
Estimate discrete choice models for mode choice.
Build activity-based and agent-based demand models.
Forecast short-term demand with statistical and machine learning techniques.
Design traffic control strategies for networks and corridors.
Evaluate demand management policies using equity criteria.
Integrate demand and control models into day-to-day operations.
Who it's for
- Transport demand modellers building choice and agent-based models.
- Traffic engineers designing network and corridor control strategies.
- Mobility planners preparing policies and mobility plans.
- Transport data analysts working with surveys, mobile and ticketing data.
- Mobility policy consultants advising public authorities.
- Traffic management centre operators responsible for daily operations.
- Engineering or science graduates looking to move into the public sector.
What you'll work with
- Directive 2010/40/EU (ITS) (framework for intelligent transport systems)
- Delegated Regulation (EU) 2017/1926 (EU-wide multimodal travel information services)
- CEN/TS 16157 (DATEX II) (traffic and travel data exchange)
- GTFS (General Transit Feed Specification) (public transport schedule and real-time data format)
- Highway Capacity Manual, 7th edition (TRB) (capacity and level-of-service methodology)
- Ley 7/2021 de cambio climático y transición energética (Spanish Climate Change and Energy Transition Act)
- SAE J2735 (V2X message set dictionary)
- Biogeme
- MATSim
- PTV Visum
- SUMO
- Python statsmodels
8 modules
1.1Trip-generating factors1.2Mobility surveys and their design1.3Mobile phone data and big data1.4Zoning and transport systems1.5Trip generation and attraction1.6Distribution with gravity models1.7Building origin-destination matrices1.8Temporal variation of demand1.9Population and land-use projections1.10Workshop: origin-destination matrix from survey data
2.1Random utility theory2.2The multinomial logit model2.3The nested logit model2.4Mixed logit and heterogeneity2.5Stated and revealed preferences2.6Value of time2.7Estimation with Biogeme2.8Elasticities and policy simulation2.9Validation of choice models2.10Lab: logit mode-choice model with Biogeme
3.1Limitations of the four-step model3.2Trip and activity chains3.3Population synthesis3.4Agent-based models with MATSim3.5Daily planning of individuals3.6Shared and on-demand mobility3.7Calibration of agent-based models3.8Computational cost of agents3.9Use in strategic planning3.10Lab: agent-based scenario in MATSim
4.1Time series of traffic counts and ticket validations4.2Seasonal and event models4.3Machine learning for forecasting4.4Graph neural networks for traffic4.5Forecasting in public transport4.6Incidents and special events4.7Forecast error metrics4.8Real-time updating4.9Integration into control centres4.10Practical: hourly forecast of metro passengers
5.1Access control with ramp metering5.2Variable speed management5.3Tolls and congestion pricing5.4Management of reversible and HOV lanes5.5Traveller information and diversions5.6Perimeter control and the MFD5.7Parking management5.8Corridor coordination5.9Evaluation of strategies5.10Lab: ALINEA ramp metering in simulation
6.1Demand management policies6.2Low-emission zones6.3Parking pricing6.4Promotion of public transport6.5Active mobility and micromobility6.6Teleworking and flexible hours6.7Mobility as a service and integrated fares6.8Equity of measures6.9Communication and social acceptance6.10Case study: effect of a low-emission zone
7.1Traffic management centres7.2Data exchange with DATEX II7.3Transport data in GTFS and GTFS-Realtime7.4Incident response plans7.5Integrated corridor management7.6Traffic decision support systems7.7Predictive simulation in operations7.8Operational indicators of the centre7.9Coordination between administrations7.10Case study: management plan for a mass event
8.1Definition of scope and objectives8.2Analysis of demand data8.3Choice or agent-based model8.4Short-term forecasting8.5Design of control strategies8.6Evaluation through simulation8.7Equity and impact analysis8.8Implementation plan for the measures8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Biogeme, MATSim, PTV Visum, SUMO and Python statsmodels, in free, academic or evaluation versions. Practical work is based on real procedures for estimating mode-choice models from surveys, forecasting public transport demand and evaluating motorway control strategies. Assessment is continuous by module, plus the final project.
Standards covered: Directive 2010/40/EU (ITS), Delegated Regulation (EU) 2017/1926, CEN/TS 16157 (DATEX II), GTFS (General Transit Feed Specification), Highway Capacity Manual, 7th edition (TRB), Ley 7/2021 de cambio climático y transición energética, SAE J2735.
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
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running 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 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Biogeme, MATSim, PTV Visum, SUMO and Python statsmodels, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, 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.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the programme software 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.
Related programmes
Diploma in Roadmap, Data SLAs and Service Contracts
Online postgraduate diploma of 800 hours in data roadmaps, data SLAs and service contracts, with 8 modules covering data product management, data roadmaps, data service levels,…
Diploma in Sensor Fusion and Cross Learning
Online postgraduate diploma of 800 hours in sensor fusion and cross-modal learning. 8 modules covering sensor fusion fundamentals, probabilistic estimation, deep learning fusion, cross-modal learning, localisation…
Diploma in Resilience and Contingency Management with DT
Online postgraduate diploma of 800 hours in resilience and contingency management with digital twins: 8 modules covering critical infrastructure resilience under Directive (EU) 2022/2557 and NIS2,…
More in Data, AI, Simulation & Analytics
All Data, AI, Simulation & Analytics programmes → · How to apply · Fees & financing · Scholarships