Air traffic demand forecasting course
About our
The Air Traffic Demand Forecasting Course focuses on the analysis and forecasting of passenger and cargo demand. It covers the use of econometric models, time series analysis, and machine learning to predict future air traffic, considering factors such as economic variables, seasonality, and global events. It focuses on the application of these methodologies for route optimization, capacity planning, and airport management, using air traffic simulation and big data tools. The course provides a solid foundation in statistics and econometrics applied to the aviation sector, enabling participants to understand and use data for strategic decision-making. Practical case studies and market research are explored to understand air traffic dynamics and their impact on airline profitability and the efficiency of flight operations. This training prepares professionals for roles such as demand analysts, route planners, and aviation consultants, enhancing their ability to forecast and adapt to market fluctuations.
Air traffic demand forecasting course
- Format: Hybrid
- Duration: 3 months
- Hours: 300 H
- Language: English / Spanish
- Registration date: 23-10-2026
- Start date: 12-12-2026
- Available places: 2
699 $
Competencies and results
What you will learn
1. Air Traffic Demand Forecasting and Analysis
- Understand the fundamentals of air traffic forecasting, including time series and econometric models.
- Evaluate the impact of factors such as seasonality, trends, and external events on demand.
- Use data analysis tools to identify patterns and trends in air traffic.
- Develop accurate forecasting models, considering key variables such as fares, capacity, and economics.
- Apply optimization techniques to improve the efficiency and profitability of air operations.
- Analyze historical air traffic data to identify significant trends and patterns.
- Interpret demand analysis reports to make strategic decisions in route and schedule planning.
- Evaluate the impact of government policies and regulations on air traffic demand.
- Master the use of specialized software and tools for demand forecasting and analysis.
- Apply The knowledge gained to optimize resource allocation and improve customer satisfaction.
2. Optimization of Rotor Modeling and Performance Evaluation
- Advanced numerical modeling and simulation of rotors.
- Analysis of rotor aeroelasticity, including phenomena such as flap-lag-torsion, whirl flutter, and their impact on structural fatigue.
- Application of cutting-edge design techniques in composite materials.
- Dimensioning and structural analysis of rotor components in composites, including the evaluation of bonded joints using finite element analysis (FEA).
- Mastery of design methodologies for damage tolerance and non-destructive testing (NDT) techniques such as ultrasonic testing (UT), radiography (RT), and thermography.
3. Comprehensive user-oriented design and validation (from modeling to manufacturing)
You will learn to integrate the entire product development process, from initial model conception to final validation, applying user-centered methodologies. You will develop skills in parametric design, ergonomics, simulation, sustainable materials, 3D visualization, and manufacturing management, ensuring efficient, safe solutions that meet current industry standards.
4. Accurate Forecasting and In-Depth Analysis of Demand in Air Transport
4. **Accurate Forecasting and In-Depth Demand Analysis in Air Transport**
- Identify and evaluate the key factors influencing air transport demand, including economic variables, seasonal factors, and external events.
- Utilize advanced modeling and forecasting techniques, such as time series, regression, and econometric models, to predict future demand with high accuracy.
- Apply big data analytics and machine learning to identify patterns and trends in demand behavior.
- Interpret and analyze forecast results to make strategic decisions in areas such as route planning, capacity management, and pricing.
- Understand the impact of market volatility and unforeseen events on demand, and develop risk mitigation strategies.
- Evaluate the performance of forecasting models and continuously optimize their accuracy and reliability.
- Apply the acquired knowledge to improve the profitability and operational efficiency of airlines.
5. Predictive Analysis and Strategic Management of Air Traffic Demand
5. Predictive Analysis and Strategic Management of Air Traffic Demand
- Forecasting air traffic demand using advanced predictive models.
- Applying time series analysis techniques to identify patterns and trends in air traffic.
- Developing demand management strategies to optimize airline and airport capacity.
- Using simulation tools to assess the impact of different scenarios on air traffic demand.
- Analyzing historical and real-time data to make strategic decisions in air traffic management.
- Understanding the role of economic, social, and environmental factors in air traffic demand.
- Evaluating the impact of unforeseen events, such as natural disasters or economic crises, on air traffic demand.
- Optimizing the allocation of resources, such as aircraft and crews, based on the Demand forecasting.
Implement pricing and promotional strategies to influence air traffic demand.
Integrate demand management with route planning and flight scheduling to maximize operational efficiency.
6. Advanced Prediction and Air Traffic Optimization Strategies
- Master the analysis of complex aerodynamic phenomena: understand and predict aircraft behavior under flap-lag-torsion couplings, analyzing their effects on aircraft stability and control. Gain in-depth knowledge of whirl flutter, a critical phenomenon in rotors and propellers, and evaluate the fatigue resistance of structural components, crucial for aircraft safety and service life.
- Apply advanced techniques in the design and analysis of composite structures: accurately dimension laminates in composites, leveraging the unique properties of these materials to optimize performance and reduce weight.
Evaluate the integrity of bonded joints and connections using finite element (FE) analysis, ensuring the strength and durability of structural connections.
Implement cutting-edge strategies for aircraft inspection and maintenance: apply damage tolerance methodologies to assess the capacity of structures to withstand damage and prevent catastrophic failures. Utilize non-destructive testing (NDT) techniques, including ultrasonic testing (UT), radiography (RT), and thermography, to detect and assess internal damage without compromising aircraft integrity, ensuring safety and optimizing maintenance programs.
Who this program is for:
Air traffic demand forecasting course
- Graduates in Aerospace Engineering, Mechanical Engineering, Industrial Engineering, Automation Engineering, or related fields.
- Professionals in OEM rotorcraft/eVTOL, MRO, consulting, and technology centers.
- Flight Testing, certification, avionics, control, and dynamics seeking specialization.
- Regulators/authorities and UAM/eVTOL professionals requiring compliance skills.
Recommended requirements: foundation in aerodynamics and control and structures; ES/EN B2+/C1. We offer bridging tracks if you need them.
- Standards-driven curriculum: you will work with CS-27/CS-29, DO-160, DO-178C/DO-254, ARP4754A/ARP4761, ADS-33E-PRF from the first module.
- Accreditable laboratories (EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
- Evidence-oriented TFM: safety case, test plan, compliance dossierand operational limits.
- Mentored by industry: teachers with experience in rotorcraft, tiltrotor, eVTOL/UAM and flight test.
- Flexible modality (hybrid/online), international cohorts and support from SEIUM Career Services.
- Ethics and security: safety-by-design approach, cyber-OT, DIH and compliance as pillars.
1.1 Fundamentals of Air Traffic Forecasting
1.2 Importance of Forecasting in the Airline Industry
1.3 Collection and Analysis of Historical Data
1.4 Basic Statistical Methods for Forecasting
1.5 Time Series Modeling for Air Demand
1.6 Key Factors Influencing Traffic Demand
1.7 Tools and Software for Traffic Forecasting
1.8 Evaluation and Validation of Predictive Models
1.9 Applications of Forecasting in Route Planning
1.10 Case Studies: Real-World Examples of Successful Forecasting
2.2 Rotor Modeling and Optimization: Fundamentals and Principles
2.2 Rotor Aerodynamics: Detailed Analysis
2.3 Rotor Blade Design: Methodologies and Tools
2.4 Numerical Rotor Modeling: CFD and Simulation
2.5 Rotor Performance Optimization: Advanced Techniques
2.6 Rotor Material Selection and Manufacturing
2.7 Structural and Vibration Analysis of Rotors
2.8 Rotor Noise: Modeling and Mitigation
2.9 Rotor Integration into Aircraft Design
2.20 Case Studies: Practical Examples of Modeling and Optimization
3.3 Introduction to Air Demand Forecasting
3.2 Fundamentals of Air Traffic Data Analysis
3.3 Key Variables Influencing Air Demand
3.4 Data Sources for Demand Forecasting
3.5 Quantitative Forecasting Methods (Time Series, Regression)
3.6 Qualitative Forecasting Methods
3.7 Tools and Software for Demand Analysis
3.8 Case Study: Demand Analysis for a Specific Airline
3.9 Introduction to Route and Pricing Optimization
3.30 Evaluating the Impact of External Events on Air Demand
4.4 Demand Forecasting and Key Factors in Air Transport
4.2 Time Series Modeling for Demand Forecasting
4.3 Data Analysis and Visualization Techniques for Air Traffic
4.4 Advanced Forecasting Methods: Machine Learning
4.5 Route and Schedule Optimization Strategies
4.6 Impact of Seasonality and Trends on Demand
4.7 Competitive and Market Analysis
4.8 Risk Assessment and Contingency Planning
4.9 Implementation of Demand Forecasting Systems
4.40 Case Studies: Practical Applications and Results
5.5 Demand Forecasting and Analysis: Introduction to Predictive Models
5.5 Data Collection and Preparation for Air Traffic
5.3 Analysis Methods: Regression, Time Series, and Machine Learning
5.4 Demand Modeling: Key Drivers and Exogenous Variables
5.5 Validation and Evaluation of Predictive Models
5.6 Demand Forecasting: Scenarios and Sensitivity Analysis
5.7 Air Traffic Analysis: Patterns, Trends, and Segmentation
5.8 Tools and Software for Air Traffic Forecasting
5.9 Optimization Strategies: Route Adjustment and Flight Scheduling
5.50 Case Study: Applying Forecasting to Strategic Decisions
6.6 Introduction to Air Traffic Optimization and Its Importance
6.2 Demand Models and Forecasting for Air Traffic
6.3 Route Optimization Strategies and Resource Allocation
6.4 Capacity Management and Traffic Flow Control
6.5 Use of Real-Time Data and Predictive Analytics
6.6 Implementation of Advanced Technologies for Optimization
6.7 Economic and Financial Aspects of Air Traffic Optimization
6.8 Regulatory Framework and Safety Considerations
6.9 Case Studies and Best Practices in Air Traffic Optimization
6.60 Future Trends and Challenges in Air Traffic Optimization
- Hands-on methodology: test-before-you-trust, design reviews, failure analysis, compliance evidence.
- Software (depending on licenses/partners): MATLAB/Simulink, Python (NumPy/SciPy), OpenVSP, SU2/OpenFOAM, Nastran/Abaqus, AMESim/Modelica, acoustics tools, planning toolchains DO-178C.
- SEIUM Laboratories: scale rotor bench, vibrations/acoustics, EMC/Lightning pre-compliance, HIL/SIL for AFCS, data acquisition with strain gauging.
- Standards and compliance: EN 9100, 17025, ISO 27001, GDPR.
Capstone-type projects
Admissions, fees, and scholarships
- Profile: Background in Computer Engineering, Mathematics, Statistics, or related fields; practical experience in NLP and valued information retrieval systems.
- Documentation: Updated CV, academic transcript, SOP/statement of purpose, project examples or code (optional).
- Process: Application → Technical evaluation of profile and experience → Technical interview → Review of case studies → Final decision → Enrollment.
- Fees:
- Single payment: 10% discount.
- Payment in 3 installments: No fees; 30% upon registration + 2 equal monthly payments of the remaining 35%.
Monthly payment: available with a 7% commission on the total; annual review.
Scholarships: based on academic merit, financial need, and promoting inclusion; agreements with companies in the sector for partial or full scholarships.
See “Calendar & Calls for Applications,” “Scholarships & Grants,” and “Fees & Financing” in the SEIUM mega-menu.
Do you have any questions?
Our team is ready to help you. Contact us, and we will respond as soon as possible.
F. A. Q
Frequently asked questions
Yes, we have international certification
Yes: experimental models, real data, applied simulations, professional environments, real case studies.
It is not mandatory. We offer leveling tracks and tutoring.
Completely. It covers e-propulsion, integration, and emerging regulations (SC-VTOL).
Recommended. There are also internal challenges and consortiums.
Yes. Online/hybrid modality with planned labs and visa support (see “Visa & Residence”).