Air traffic demand forecasting course
Online course of 300 hours in air traffic demand forecasting. 6 modules covering air transport demand, time-series forecasting, econometric and network models, applied machine learning and application to planning, with 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
Identify the determinants of air transport demand.
Apply time-series models to traffic data.
Build econometric and gravity demand models.
Use machine learning techniques for forecasting.
Assess forecast accuracy with appropriate metrics.
Translate forecasts into infrastructure needs.
Produce a demand forecast for a real airport.
Who it's for
- Air transport demand analysts
- Airline network planners
- Airport data analysts
- Airport planning consultants
- Transport economists
- Aviation data scientists
- Engineering or science graduates looking to join airport operators
What you'll work with
- ICAO Doc 8991 Manual on Air Traffic Forecasting (ICAO guidance on traffic forecasting methods)
- Regulation (EEC) 95/93 on the allocation of slots (common rules for slot allocation at EU airports)
- IATA Worldwide Airport Slot Guidelines (WASG) (global slot coordination standards)
- Commission Implementing Regulation (EU) 2019/317 on performance and charging (SES performance and charging scheme)
- ICAO Doc 9184 Airport Planning Manual (airport master planning guidance)
- Commission Implementing Regulation (EU) 2019/123 on the Network Manager (network functions of air traffic management)
- Python with statsmodels
- R with the forecast package
- Prophet
- OAG Schedules Analyser
- Cirium
6 modules
1.1Economic determinants of demand1.2Price and income elasticities1.3Passenger segments and travel purposes1.4Air cargo demand1.5Seasonality and economic cycles1.6Effect of crises and external shocks1.7Traffic data sources1.8Passenger and movement indicators1.9Forecasting horizons and uses1.10Case study: historical analysis of an airport
2.1Decomposition of traffic series2.2Holt-Winters exponential smoothing2.3ARIMA and SARIMA models2.4Intervention variables and outliers2.5Handling structural breaks2.6Time-series cross-validation2.7MAPE and RMSE error metrics2.8Short-term operational forecasting2.9Prediction intervals2.10Lab: SARIMA model with passenger data
3.1Regression models with macroeconomic variables3.2Gravity models of traffic3.3Discrete choice logit models3.4Competition between airports3.5Origin–destination demand matrices3.6Airline networks and connections3.7Building macroeconomic scenarios3.8Competition with high-speed rail3.9Elasticity to charges and taxes3.10Workshop: gravity model of routes
4.1Decision trees and gradient boosting4.2LSTM recurrent neural networks4.3Additive models with Prophet4.4Feature selection and engineering4.5Overfitting and regularisation4.6Forecast combination4.7Peak-hour forecasting4.8Model interpretability4.9Deploying models in production4.10Practical exercise: comparing forecasting models
5.1EUROCONTROL STATFOR forecasts5.2Design peak hour for infrastructure5.3Capacity and slot coordination5.4Traffic forecasting for ATM5.5Long-term planning scenarios5.6Demand risk and uncertainty5.7Communicating forecasts to decision-makers5.8Reviewing past forecasts5.9Forecasts for master plans5.10Case study: forecast for a master plan
6.1Selecting the case study6.2Data collection and cleaning6.3Exploratory analysis of the series6.4Selecting candidate models6.5Validation and error comparison6.6Building scenarios6.7Final forecast with intervals6.8Implications for infrastructure6.9Report and presentation6.10Final project: final review with the tutor
How you'll learn
Training is 100% online 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 Python with statsmodels, R with the forecast package, Prophet, OAG Schedules Analyser and Cirium, in free, academic or evaluation versions. Exercises are based on real procedures: monthly passenger forecasting with SARIMA, a gravity model of demand between cities and comparing machine learning models for traffic. Assessment is continuous by module, plus the final integrating project.
Standards covered: ICAO Doc 8991 Manual on Air Traffic Forecasting; Regulation (EEC) 95/93 on the allocation of slots; IATA Worldwide Airport Slot Guidelines (WASG); Commission Implementing Regulation (EU) 2019/317 on performance and charging; ICAO Doc 9184 Airport Planning Manual; Commission Implementing Regulation (EU) 2019/123 on the Network Manager.
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 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 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 Python with statsmodels, R with the forecast package, Prophet, OAG Schedules Analyser and Cirium, 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 an internet connection, a computer capable of running 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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