Synthetic data generation course
About our
The Synthetic Data Generation Course focuses on the creation and use of artificial datasets for various applications. It explores advanced techniques in machine learning, statistics, and simulation to generate realistic and useful data. It focuses on the application of this synthetic data in areas such as AI model training, software testing, and predictive analytics, especially in scenarios where real data is scarce, expensive, or sensitive.
The course offers hands-on experience using specialized tools and libraries for synthetic data generation, including methods for data modeling, event simulation, and data anonymization. This training prepares professionals for roles such as data scientists, machine learning engineers, and data analysts, enabling the development of innovative solutions in the industry.
Synthetic data generation 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
499 $
Competencies and results
What you will learn
1. Mastery of Synthetic Data Generation for Innovation
**What will you learn in the course: Mastering Synthetic Data Generation for Innovation?**
Below, we present the knowledge and skills you will acquire in this course:
- Understand and apply advanced techniques for creating synthetic data.
- Generate high-quality synthetic datasets for training Machine Learning models.
- Use specialized tools and platforms for generating synthetic data.
- Evaluate and validate the usefulness of synthetic data for different applications.
- Apply synthetic data to optimize innovation and development processes.
2. Evaluation and optimization of rotor performance
## What Will You Learn?
2. Rotor Performance Evaluation and Optimization
- Analyze flap-lag-torsion, whirl flutter, and fatigue couplings.
- Dimension laminates in composites, joints, and bonded joints with FE.
- Implement damage tolerance and NDT (UT/RT/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. Simulation and data analysis for rotors
4. Simulation and Data Analysis for Rotors
- Analyze flap-lag-torsion, whirl flutter, and fatigue couplings.
- Dimension laminates in composites, joints, and bonded joints with FE.
- Implement damage tolerance and NDT (UT/RT/thermography).
5. Development of skills for rotor simulation
5. Development of skills for rotor simulation
- Analyze flap-lag-torsion, whirl flutter, and fatigue couplings.
- Dimension laminates in composites, joints, and bonded joints using FE.
- Implement damage tolerance and NDT (UT/RT/thermography).
6. Implementation of Advanced Techniques in Rotor Modeling
6. Implementation of Advanced Techniques in Rotor Modeling
- Analyze flap–lag–torsion couplings, whirl flutter and fatigue.
- Size laminates in composites, unions and bonded joints with FE.
- Implement damage tolerance and NDT (UT/RT/thermography).
Who this program is for:
Synthetic data generation 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.
2.1 Fundamentals of Synthetic Data Generation
2.2 Applications of Synthetic Data Generation in Naval Engineering
2.3 Tools and Software for Synthetic Data Generation
2.4 Design of Experiments and Sampling Strategies
2.5 Quality of Synthetic Data: Validation and Verification
2.6 Implementation of Synthetic Data in Rotor Analysis
2.7 Ethics and Legal Considerations in Data Generation
2.8 Case Studies: Successes and Challenges
2.9 Future of Synthetic Data Generation in the Naval Industry
2.10 Seminar: Practical Applications
2.2 Fundamentals of Synthetic Data Generation for Rotors
2.2 Synthetic Data Generation Techniques for Simulation
2.3 Validation and Verification of Synthetic Data
2.4 Optimizing the Simulation Workflow with Synthetic Data
2.5 Sensitivity Analysis and Design of Experiments with Synthetic Data
2.6 Application of Synthetic Data in Rotor Design
2.7 Integration of Synthetic Data into Performance Analysis
2.8 Advanced Techniques in Synthetic Data Generation
2.9 Tools and Software for Synthetic Data Generation
2.20 Case Studies: Real-World Applications of Synthetic Data in Rotors
3.3 Fundamentals of Rotor Design: Principles and Geometry
3.2 Generation of Synthetic Data for Rotor Design
3.3 3D Modeling and CAD Design of Rotors
3.4 CFD Simulation for Rotor Analysis
3.5 Structural and Dynamic Analysis of Rotors
3.6 Rotor Performance Optimization
3.7 Evaluation of Energy Efficiency and Aerodynamics
3.8 Failure Analysis and Failure Modes in Rotors
3.9 Integration of Rotors into Propulsion Systems
3.30 Life Cycle and Cost Analysis of Rotors
4.4 Introduction to Rotor Simulation: Fundamentals and Tools
4.2 Rotor Modeling and Configuration in Simulation Software
4.3 Rotor Airflow and Aerodynamic Simulation
4.4 Results Analysis: Data Interpretation and Key Parameters
4.5 Advanced Simulation Techniques: CFD and High-Fidelity Models
4.6 Validation of Simulation Models: Comparison with Experimental Data
4.7 Rotor Design Optimization through Simulation
4.8 Stability and Control Analysis of Simulated Rotors
4.9 Rotor Failure Simulation and Risk Analysis
4.40 Applications of Rotor Simulation in the Shipbuilding Industry
5.5 Introduction to Synthetic Data in the Naval Field
5.5 Sources and Types of Synthetic Data
5.3 Applications of Synthetic Data in Naval Simulation
5.4 Tools and Techniques for Generating Synthetic Data
5.5 Validation and Verification of Synthetic Data
5.6 Case Studies: Synthetic Data in Naval Scenarios
5.7 Challenges and Limitations of Synthetic Data
5.8 Ethics and Privacy in the Generation and Use of Synthetic Data
5.9 Future Trends in the Generation and Application of Synthetic Data
5.50 Practical Exercises: Generation and Analysis of Synthetic Data
5.5 Introduction to the Evaluation of Naval Rotor Performance
5.5 Key Performance Metrics: Thrust, Efficiency, Noise, etc.
5.3 Evaluation Methodologies: Wind Tunnel Testing, CFD, etc.
5.4 Factors Influencing Rotor Performance
5.5 Performance Optimization: Strategies and Techniques
5.6 Software and Tools for Evaluation and Optimization
5.7 Case Studies: Rotor Optimization in Different Naval Applications
5.8 Design of Experiments for Performance Optimization
5.9 Sensitivity and Robustness Analysis in Optimization
5.50 Practical Exercises: Evaluation and Optimization of a Rotor
3.5 Principles of Naval Rotor Design
3.5 Rotor Geometry: Blade and Airfoil Design
3.3 Computer-Aided Design (CAD) Tools for Rotors
3.4 Aerodynamic Analysis of Rotors: Theory and Numerical Methods
3.5 Structural Design of Rotors: Materials and Strength
3.6 Hydrodynamic Analysis of Rotors
3.7 Cavitation and Noise Considerations in Design 3.8 Iterative Design Process: Design, Analysis, and Optimization
3.9 Design for Manufacturing and Assembly
3.50 Practical Exercises: Design of a Naval Rotor
4.5 Introduction to Rotor Data Simulation
4.5 Numerical Simulation Methods: CFD, BEM, etc.
4.3 Data Preparation for Simulation: Meshing, Boundary Conditions, etc.
4.4 Simulation Setup and Execution
4.5 Analysis of Simulation Results: Visualization and Post-Processing
4.6 Validation of Simulation Results: Comparison with Experimental Data
4.7 Applications of Simulation in Rotor Design and Analysis
4.8 Simulation Tools and Software
4.9 Interpretation of Simulated Data
4.50 Practical Exercises: Simulation and Analysis of a Rotor
5.5 Introduction to Rotor Simulation: Key Concepts 5.5 Selection and configuration of simulation tools.
5.3 Simplified rotor modeling: approximations and assumptions.
5.4 Meshing and discretization: techniques and considerations.
5.5 Definition of boundary conditions and simulation parameters.
5.6 Execution and monitoring of simulations.
5.7 Analysis of basic results: forces, moments, etc.
5.8 Interpretation of results and resolution of common problems.
5.9 Best practices for rotor simulation.
5.50 Practical exercises: basic rotor simulation.
6.5 Advanced rotor modeling techniques: flexible blade modeling.
6.5 Modeling fluid-structure interaction phenomena.
6.3 Modeling cavitation and other multiphysics effects.
6.4 Modeling noise and vibration.
6.5 Simulation-based optimization techniques. 6.6 Rotor Modeling in Complex Scenarios: Hull Interaction, etc.
6.7 Rotor Modeling under Extreme Operating Conditions
6.8 Advanced Tools and Software for Rotor Modeling
6.9 Uncertainty and Robustness Analysis in Modeling
6.50 Practical Exercises: Advanced Rotor Modeling
7.5 Introduction to Predictive Analytics Applied to Rotors
7.5 Predictive Models: Machine Learning, Neural Networks, etc.
7.3 Data Collection and Preparation for Predictive Analytics
7.4 Training and Validation of Predictive Models
7.5 Applications of Predictive Analytics: Performance Optimization, Fault Detection, etc.
7.6 Time Series Analysis Techniques for Rotor Data
7.7 Real-Time Data Analysis and Decision Making
7.8 Tools and Software for Predictive Analytics 7.9 Implementation of predictive models in naval systems.
7.50 Practical exercises: construction and application of a predictive model.
8.5 Introduction to synthetic data for rotor simulation.
8.5 Generation of synthetic data for simulation: methods and tools.
8.3 Simulation with synthetic data: generation of scenarios and conditions.
8.4 Use of synthetic data for model training.
8.5 Applications of synthetic data in rotor simulation.
8.6 Validation and verification of simulations with synthetic data.
8.7 Generation of synthetic datasets for sensitivity analysis.
8.8 Optimization of algorithms using synthetic data.
8.9 Challenges and opportunities of synthetic data in simulation.
8.50 Practical exercises: generation and use of synthetic data in simulation.
6.6 eVTOL and UAM: Electric Propulsion, Multiple Rotors
6.2 Emerging Certification Requirements (SC-VTOL, Special Conditions)
6.3 Energy and Thermal in E-Propulsion (Batteries/Inverters)
6.4 Design for Maintainability and Modular Swaps
6.5 LCA/LCC in Rotorcraft and eVTOL (Footprint and Cost)
6.6 Operations & Vertiports: Airspace Integration
6.7 Data & Digital Thread: MBSE/PLM for Change Control
6.8 Tech Risk and Readiness: TRL/CRL/SRL
6.9 IP, Certifications, and Time-to-Market
6.60 Case Study: Go/No-Go with Risk Matrix
- 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”).