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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.

Duration6–8 months
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
Enrol now View syllabus Ask an advisor

Diploma in Demand Models and Control Strategies — studying from India

India's data and analytics capability is among the largest in the world, with major centres in Bengaluru, Hyderabad, Pune, Chennai and Gurugram. Global technology firms and domestic IT companies such as Tata Consultancy Services, Infosys, Wipro and HCLTech run large engineering and analytics operations. Engineering organisations increasingly apply AI, simulation and digital twin techniques to product design and manufacturing. Data protection rules are shaped by the Ministry of Electronics and Information Technology, while the National Association of Software and Service Companies represents the sector. Engineers here build models, analytics pipelines and simulation workflows across industries.

Fees for India: ₹116,000 (Indian Rupee), with instalments and employer sponsorship available.

Relevant bodies in India

  • Ministry of Electronics and Information Technology (MeitY)
  • National Association of Software and Service Companies (NASSCOM)
  • Bureau of Indian Standards (BIS)
  • Indian Statistical Institute

Typical roles

  • Data Scientist
  • Machine Learning Engineer
  • Simulation Engineer
  • Data Analytics Engineer

Questions from India

Are there professional bodies in India that recognise data and AI engineering?

India does not have a statutory licence for data scientists or AI engineers. Relevant professional bodies include the Computer Society of India (CSI), the Institution of Engineers (India) and IEEE India sections. SEIUM's qualifications are private, not state degrees and not accredited by a national body, so their value depends on how employers view them.

Which employers in India hire data and AI professionals?

Demand is strong in IT services and consulting firms, banks and fintech companies, e-commerce and healthcare organisations, and research labs, especially in Bengaluru, Hyderabad, Pune and the NCR. A private online programme can support a career change or upskilling, but employers mainly assess coding, statistics and project portfolios alongside your qualifications.

Can I study this while working full time in India?

Yes. The programme is fully online and taught in English, so you can study from home without a student visa. Schedules are set in IST, so plan around your working hours. Specialist courses are about 300 hours, diplomas 800 and master's about 1,900. Each student has an assigned technical tutor, and fees can be paid in instalments. Ask your employer whether they will sponsor the fees.

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Learning outcomes

What you will be able to do

01

Analyse mobility demand from surveys and big data.

02

Estimate discrete choice models for mode choice.

03

Build activity-based and agent-based demand models.

04

Forecast short-term demand with statistical and machine learning techniques.

05

Design traffic control strategies for networks and corridors.

06

Evaluate demand management policies using equity criteria.

07

Integrate demand and control models into day-to-day operations.

Profile

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.
Standards & tools

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
Syllabus

8 modules

  1. 1.1Trip-generating factors
  2. 1.2Mobility surveys and their design
  3. 1.3Mobile phone data and big data
  4. 1.4Zoning and transport systems
  5. 1.5Trip generation and attraction
  6. 1.6Distribution with gravity models
  7. 1.7Building origin-destination matrices
  8. 1.8Temporal variation of demand
  9. 1.9Population and land-use projections
  10. 1.10Workshop: origin-destination matrix from survey data
  1. 2.1Random utility theory
  2. 2.2The multinomial logit model
  3. 2.3The nested logit model
  4. 2.4Mixed logit and heterogeneity
  5. 2.5Stated and revealed preferences
  6. 2.6Value of time
  7. 2.7Estimation with Biogeme
  8. 2.8Elasticities and policy simulation
  9. 2.9Validation of choice models
  10. 2.10Lab: logit mode-choice model with Biogeme
  1. 3.1Limitations of the four-step model
  2. 3.2Trip and activity chains
  3. 3.3Population synthesis
  4. 3.4Agent-based models with MATSim
  5. 3.5Daily planning of individuals
  6. 3.6Shared and on-demand mobility
  7. 3.7Calibration of agent-based models
  8. 3.8Computational cost of agents
  9. 3.9Use in strategic planning
  10. 3.10Lab: agent-based scenario in MATSim
  1. 4.1Time series of traffic counts and ticket validations
  2. 4.2Seasonal and event models
  3. 4.3Machine learning for forecasting
  4. 4.4Graph neural networks for traffic
  5. 4.5Forecasting in public transport
  6. 4.6Incidents and special events
  7. 4.7Forecast error metrics
  8. 4.8Real-time updating
  9. 4.9Integration into control centres
  10. 4.10Practical: hourly forecast of metro passengers
  1. 5.1Access control with ramp metering
  2. 5.2Variable speed management
  3. 5.3Tolls and congestion pricing
  4. 5.4Management of reversible and HOV lanes
  5. 5.5Traveller information and diversions
  6. 5.6Perimeter control and the MFD
  7. 5.7Parking management
  8. 5.8Corridor coordination
  9. 5.9Evaluation of strategies
  10. 5.10Lab: ALINEA ramp metering in simulation
  1. 6.1Demand management policies
  2. 6.2Low-emission zones
  3. 6.3Parking pricing
  4. 6.4Promotion of public transport
  5. 6.5Active mobility and micromobility
  6. 6.6Teleworking and flexible hours
  7. 6.7Mobility as a service and integrated fares
  8. 6.8Equity of measures
  9. 6.9Communication and social acceptance
  10. 6.10Case study: effect of a low-emission zone
  1. 7.1Traffic management centres
  2. 7.2Data exchange with DATEX II
  3. 7.3Transport data in GTFS and GTFS-Realtime
  4. 7.4Incident response plans
  5. 7.5Integrated corridor management
  6. 7.6Traffic decision support systems
  7. 7.7Predictive simulation in operations
  8. 7.8Operational indicators of the centre
  9. 7.9Coordination between administrations
  10. 7.10Case study: management plan for a mass event
  1. 8.1Definition of scope and objectives
  2. 8.2Analysis of demand data
  3. 8.3Choice or agent-based model
  4. 8.4Short-term forecasting
  5. 8.5Design of control strategies
  6. 8.6Evaluation through simulation
  7. 8.7Equity and impact analysis
  8. 8.8Implementation plan for the measures
  9. 8.9Report and presentation
  10. 8.10Final project: final review with the tutor
Methodology, software & labs

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.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of Directive 2010/40/EU, Delegated Regulation (EU) 2017/1926 and DATEX II applied to real cases, not as a theoretical annex.
Industry software:Biogeme, MATSim, PTV Visum, SUMO and Python statsmodels, in free, academic or evaluation versions.
Final project:a demand model combined with control strategies for a real area, evaluated through simulation with equity and impact analysis, reviewed by your tutor.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Scope and demand data
Define the scope and objectives and analyse the demand data.
Demand model
Build a discrete choice or agent-based model of the area.
Forecasting and control
Forecast short-term demand and design control strategies.
Simulation and equity
Evaluate the strategies through simulation, with equity and impact analysis.
Final project
Present the implementation plan in a report and presentation, reviewed by your tutor.
Career opportunities

Where this takes you

Transport demand modellerTraffic engineerMobility plannerTransport data analystMobility policy consultantTraffic management centre operator
Admissions & scholarships

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.

Apply now Scholarships
FAQ

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.

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