Track data acquisition course
Track Data Acquisition Course
This course focuses on mastering sensor and data acquisition (DAQ) technologies for monitoring and analyzing moving vehicles. It provides in-depth knowledge of the implementation and calibration of acceleration sensors, force sensors, and GPS systems to capture relevant data in real time, as well as the analysis of that data. The course covers everything from hardware configuration to signal interpretation, including the use of specialized software for data processing and visualization, making it ideal for test engineers and automotive technicians.
The program includes hands-on experience in real-world scenarios, focusing on system validation, fault identification, and performance optimization. Participants will learn to apply data filtering, spectral analysis, and statistical methods to extract valuable information about vehicle behavior, as well as knowledge of communication protocols such as CAN bus. The course fosters an understanding of safety regulations and traction control systems, preparing professionals for application in the automotive industry, motorsport, and the development of autonomous vehicles.
Take the controls.
Run a real engineering trade-off from this programme. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Acquisition and Analysis of Runway Data for Naval Optimization
Rotor Modeling and Performance for Naval Efficiency
Comprehensive user-oriented design and validation (from modeling to manufacturing)
Naval Optimization: Runway Data Acquisition
Optimization of Runway Data for Naval Engineering
On-Site Data Collection for Naval Engineering
Naval Optimization Through Runway Data Acquisition
Runway Data Analysis for Naval Strategies
Who it's for
- Graduates in Aerospace Engineering, Mechanical, Industrial, Automatics or similar.
- OEM rotorcraft/eVTOL professionals, MRO, consulting, technology centers.
- Flight Test, certification, avionics, control and dynamics who seek specialization.
- Regulators/authorities and UAM/eVTOL profiles that require compliance competencies.
What you'll work with
- 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.
10 modules
1.1Introduction to Data Collection in Naval Environments1.2Sensors and Data Acquisition (DAQ) Systems1.3Types of Data Relevant to Naval Engineering1.4Data Acquisition Methodology at Sea1.5Sensor Calibration and Verification1.6Storage and Management of Collected Data1.7Principles of Data Quality1.8Software Tools for Initial Analysis1.9Ethics and Safety Considerations in Data Collection1.10Application Examples in Naval Projects
2.2Principles of Rotor Aerodynamics3.2Design and Analysis of Airfoil Profiles4.3CFD Modeling of Flow in Rotors5.4Rotor Performance Simulation6.5Selection and Design of Propulsion Systems7.6Optimization of Rotor Geometry8.7Energy Efficiency Evaluation9.8Vibration and Noise Analysis20.9Rotor Materials and Manufacturing22.20Case Studies: Naval Applications
3.3Introduction to Runway Data Collection and Analysis3.2Sensors and Data Acquisition Systems for Naval Environments3.3Methodology for Data Collection in Maritime Environments3.4Processing and Cleaning of Runway Data Collection3.5Statistical Data Analysis for Naval Optimization3.6Visualization and Graphical Representation of Naval Data3.7Applications of Runway Data Acquisition: Case Studies3.8Optimizing Naval Design Through Data Analysis3.9Data-Based Strategies for Improving Naval Performance3.30The Future of Data Collection and Analysis in Naval Engineering
4.4Fundamentals of Data Acquisition in the Naval Context4.2Sensors and Equipment: Selection and Use for Data Collection4.3Data Acquisition Methodologies in Marine Environments4.4Calibration and Validation of Data in Naval Systems4.5Introduction to Data Analysis for Naval Optimization4.6Identification of Key Variables for Naval Performance4.7Data-Driven Optimization Techniques4.8Case Studies: Application of Data-Driven Optimization in Naval Contexts4.9Software Tools for Naval Data Acquisition and Analysis4.40Design of Experiments for Naval Performance Optimization
5.5Fundamentals of Runway Data Acquisition for Naval Engineering5.5Sensors and Measurement Systems for Data Collection in Naval Environments5.3Runway Data Analysis Methodologies for Naval Optimization5.4Applications of Data Acquisition in Optimizing Ship Efficiency5.5Data Analysis for the Design of Optimized Hulls and Naval Structures5.6Use of Runway Data for Improving the Performance of Naval Propulsion Systems5.7Implementation of Naval Strategies Based on Runway Data Analysis5.8Design of Experiments and Test Planning in the Naval Environment5.9Visualization and Communication of Data Results for Decision Making5.50Practical Cases of Naval Optimization Using Runway Data Analysis
6.6Data Collection Sources and Methods in Naval Engineering6.2Instrumentation and Sensors for Data Acquisition in Naval Environments6.3Design of Experiments for Data Collection in Naval Trials6.4Data Collection and Storage Protocols on Vessels6.5Calibration and Validation of Data Collected at Sea6.6Safety and Data Protection Considerations in Naval Environments6.7Applications of Data Collection in Naval Design and Optimization6.8Error Analysis and Handling of Incomplete Data6.9Implementation of Data Collection Systems Onboard Ships6.60Case Studies: Practical Examples of Data Collection in Naval Projects
7.7Introduction to Runway Data Acquisition for Naval Engineering7.2Runway Data Sources: Sensors and Systems7.3Runway Data Collection Methodologies7.4Processing and Cleaning Collected Data7.7Statistical Data Analysis for Naval Engineering7.6Data Visualization for Decision Making7.7Optimization Applications: Design and Performance7.8Case Studies: Optimization in Naval Projects7.9Data Integration in the Naval Design Process7.70Tools and Software for Data Analysis
8.8Runway Data Collection and Analysis: Fundamentals8.8Data Sources: Sensors and Acquisition Systems8.3Data Cleaning and Preprocessing for Naval Analysis8.4Data Visualization for Strategic Decision Making8.5Descriptive Data Analysis in the Naval Context8.6Comparative Analysis and Trends in the Naval Field8.7Identifying Patterns and Anomalies in Runway Data8.8Applying Predictive Models to Naval Strategies8.8Data-Based Risk and Opportunity Assessment8.80Case Studies: Analysis of Successful and Failed Naval Strategies
9.9Fundamentals of Naval Data Acquisition9.9Sensors and Measurement Systems in the Naval Environment9.3Planning and Execution of On-Skip Data Collection9.4Data Calibration and Validation9.5Introduction to Data Analysis Tools9.9Principles of Rotor Modeling9.9Rotor Performance Analysis Techniques9.3Numerical Simulation and CFD in Rotor Analysis9.4Optimizing Rotor Design for Efficiency9.5Evaluating and Comparing Different Rotor Designs3.9Gathering Relevant Data for Naval Design3.9Data Analysis Techniques for Design Optimization3.3Using Data in the Conceptual Design Phase3.4Integrating Data into the Detailed Design Process3.5Software Tools for Naval Design Data Analysis4.9Principles of Naval Optimization4.9The Role of Data Acquisition in Optimization4.3Designing and Planning Tests for Data Acquisition Data4.4Data Analysis for Naval Performance Improvement4.5Applying Results to Operations Optimization5.9Importance of Data Optimization in Naval Engineering5.9Relevant Data Sources and Types in Naval Engineering5.3Methods for Data Optimization5.4Data Analysis for Engineering Decision Making5.5Implementing Data Optimization in Naval Projects6.9Planning and Preparation for Data Collection6.9Equipment and Techniques for Data Collection6.3Managing and Storing Collected Data6.4Data Quality Control and Validation6.5Safety and Regulatory Considerations7.9Data-Based Naval Optimization Strategies7.9Data Acquisition Methods for Naval Optimization7.3Analysis and Interpretation of Track Data7.4Optimizing Performance and Efficiency7.5Implementing Data-Based Improvements8.9Developing Data-Based Naval Strategies8.9Data Analysis for Decision Making Strategic8.3Identification of Key Performance Indicators (KPIs)8.4Evaluation of the Impact of Naval Strategies8.5Adaptation of Strategies Based on Data
1.1Runway Data Collection: Fundamentals for Naval Optimization1.2Design of Instrumentation and Sensors for the Naval Environment1.3Data Acquisition Techniques in Marine Environments1.4Runway Data Analysis: Introduction to Tools and Methods1.5Data Validation and Calibration for Naval Engineering1.6Design of Experiments for Naval Performance Optimization1.7Statistical Analysis Applied to Naval Data1.8Interpretation and Visualization of Runway Data1.9Case Studies: Practical Application in Naval Design1.10Final Project: Comprehensive Runway Data Analysis2.1Principles of Naval Rotor Aerodynamics2.2Numerical Modeling of Flow around Rotors2.3Airfoil Design for Naval Efficiency2.4Rotor Performance Simulation2.5Rotor Geometry Optimization2.6Analysis of Interference Effects in Systems Rotors2.7Energy Performance Evaluation2.8Noise Reduction in Naval Propulsion Systems2.9Case Studies: Rotor System Optimization2.10Final Project: Rotor Modeling and Optimization3.1Relevant Data Sources for Naval Design3.2Data Collection Methods in Naval Environments3.3Data Cleaning and Preprocessing3.4Exploratory Data Analysis for Design3.5Data Modeling to Predict Performance3.6Design of Experiments to Evaluate Naval Design3.7Data Analysis to Improve Stability3.8Design and Data Analysis to Improve Maneuverability3.9Cost-Benefit Analysis for Design3.10Final Project: Optimized Naval Design4.1Data Acquisition Strategies4.2Design of Experiments for Naval Optimization4.3Sensors and Measurement Systems for the Optimization4.4Data Acquisition Techniques4.5Exploratory Data Analysis for Optimization4.6Naval Performance Data Analysis4.7Performance Modeling4.8Data Validation and Verification4.9Optimization Case Studies4.10Final Project: Naval Optimization5.1Collection of Relevant Data5.2Instrumentation Design5.3Data Cleaning and Preprocessing5.4Exploratory Data Analysis5.5Performance Modeling5.6Design Optimization5.7Risk Analysis5.8Implementation and Testing5.9Performance Evaluation5.10Final Project: Naval Engineering6.1Relevant Data Sources for Naval Engineering6.2Design of Experiments for Data Collection6.3Instrumentation and Sensors in Naval Environments6.4Data Collection Methods6.5Data Validation and Calibration6.6Analysis of Data6.7Performance Modeling6.8Data Visualization and Interpretation6.9Data Collection Case Studies6.10Final Project: Data Collection7.1Optimization Fundamentals7.2Design of Experiments7.3Sensors and Acquisition Systems7.4Acquisition Techniques7.5Cleaning and Preprocessing7.6Data Analysis7.7Performance Modeling7.8Implementation of Optimization Strategies7.9Evaluation of Results7.10Final Project: Naval Optimization8.1Types of Data Relevant to Naval Strategies8.2Data Collection Methods at Sea8.3Cleaning and Preprocessing8.4Exploratory Analysis8.5Statistical Analysis and Visualization8.6Modeling and Simulation8.7Data-Driven Decision Making8.8Development of Naval Strategies8.9Evaluation of Results8.10Final Project: Data Analysis
How you'll learn
- 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.
Where this takes you
Requirements
- 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.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
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”).
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