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Diploma in Risk Analysis and Monte Carlo in Planning

The Diploma in Risk Analysis and Monte Carlo in Planning provides specialized knowledge in the application of risk analysis and Monte Carlo simulation for optimizing project planning. The program focuses on the identification, assessment, and mitigation of risks, using quantitative techniques for estimating uncertainty and analyzing scenarios in project management. Tools for modeling and simulating variables are included, enabling more informed decision-making and improved planning efficiency.

Participants acquire skills to apply these methodologies in various sectors, from engineering and construction to financial management and strategic planning. The training emphasizes hands-on experience using specialized software and data analysis, preparing professionals to anticipate and manage the risks inherent in any project and improve decision-making in complex and uncertain environments, with a focus on achieving objectives.

Duration6–8 months
ModeOnline
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Mastery of Risk Analysis and Monte Carlo Modeling for Strategic Planning

02

Implementation of Risk Analysis and Monte Carlo Modeling in Planning and Management

03

Comprehensive user-oriented design and validation (from modeling to manufacturing)

04

In-depth Risk Assessment and Monte Carlo Simulation in Effective Planning

05

Expert Implementation of Monte Carlo and Risk Analysis for Reliable Planning

06

Practical Application of Risk Analysis and Monte Carlo Modeling in Comprehensive Planning

07

Master Planning Driven by Risk Analysis and Monte Carlo Simulation

08

Integrating Risk Analysis and Monte Carlo Modeling for Planning and Decision Making

Profile

Who it's for

  • Professionals and graduates in areas related to **project planning and management**, including, but not limited to, **Engineering**, **Economics**, **Business Administration**, and related fields.
  • Risk analysts, project managers, and planning personnel seeking to **improve their skills in risk assessment and mitigation** through the use of Monte Carlo simulation.
  • Individuals interested in **financial analysis**, **strategic decision-making**, and **resource optimization**, who wish to apply advanced techniques for **scenario forecasting** and **uncertainty management**.
  • Consultants and advisors who need to offer **high-quality services** in the identification, assessment, and management of risks to their clients.
Recommended requirements: Basic knowledge of probability and statistics.
Standards & tools

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.
Syllabus

10 modules

  1. 1.1Introduction to Risk Analysis in Naval Strategic Planning.
  2. 1.2Fundamentals of Monte Carlo Simulation: Concepts and Applications.
  3. 1.3Risk Identification and Assessment: Methodologies and Tools.
  4. 1.4Introduction to Data Modeling for Simulation.
  5. 1.5Risk Variables: Types and Classification in the Naval Context.
  6. 1.6The Monte Carlo Simulation Process: Key Steps.
  7. 1.7Interpretation of Results: Sensitivity Analysis and Scenarios.
  8. 1.8Applications of Risk Analysis and Monte Carlo in Naval Planning.
  9. 1.9Tools and Software for Risk Analysis.
  10. 1.10Case Studies: Practical Examples in Naval Planning.
  1. 2.2Introduction to Risk Analysis in Strategic Planning
  2. 2.2Fundamentals of Monte Carlo Simulation
  3. 2.3Risk Identification and Assessment in Naval Projects
  4. 2.4Data Collection and Analysis Techniques for Risks
  5. 2.5Risk Model Development: First Steps
  6. 2.6Probability and Distributions in Risk Analysis
  7. 2.7Tools and Software for Risk Analysis
  8. 2.8Interpretation of Results and Decision Making
  9. 2.9Practical Applications in Naval Planning
  10. 2.20Case Study: Risk Analysis in a Specific Project
  11. 2.2Integration of Risk Analysis into Project Management
  12. 2.2Implementation of Monte Carlo Simulation in Operational Management
  13. 2.3Real-Time Risk Monitoring and Control
  14. 2.4Uncertainty and Variability Management
  15. 2.5Risk Mitigation and Response Strategies
  16. 2.6Use of Historical Data for Risk Management Risks
  17. 2.7Integrating Risks into Resource Planning
  18. 2.8Sensitivity Analysis and Scenarios
  19. 2.9Assessing the Impact of Risks on the Budget
  20. 2.20Advanced Risk Management Software and Tools
  21. 3.2Optimizing Planning through Risk Analysis
  22. 3.2Applying Monte Carlo Simulation for Optimization
  23. 3.3Design of Experiments and Scenario Analysis
  24. 3.4Determining the Critical Path with Risks
  25. 3.5Optimization Techniques for Risk Mitigation
  26. 3.6Cost-Benefit Analysis in Risk Management
  27. 3.7Continuous Improvement in Strategic Planning
  28. 3.8Using Simulation for Decision Making
  29. 3.9Implementing Key Performance Indicators (KPIs)
  30. 3.20Practical Cases of Optimization in Naval Projects
  31. 4.2In-Depth Risk Assessment: Advanced Methodologies
  32. 4.2Application of Monte Carlo Simulation in Complex Scenarios
  33. 4.3Quantitative and Qualitative Risk Analysis
  34. 4.4High-Complexity Risk Assessment
  35. 4.5Risk Modeling with Multiple Variables
  36. 4.6Sensitivity Analysis and Monte Carlo Simulations
  37. 4.7Model Validation and Verification Techniques
  38. 4.8Advanced Interpretation of Results and Reports
  39. 4.9Implementation of Risk Models in Decision Making
  40. 4.20Case Study: Risk Assessment in Critical Projects
  41. 5.2Expert Monte Carlo Implementation: Advanced Techniques
  42. 5.2Integration of Risk Analysis into Strategic Planning
  43. 5.3Risk Modeling and Simulation with Specialized Software
  44. 5.4Scenario Development and Sensitivity Analysis
  45. 5.5Risk-Based Optimization Techniques
  46. 5.6Decision Making Under Uncertainty
  47. 5.7Risk Management in Large-Scale Projects
  48. 5.8Developing Effective Contingency Plans
  49. 5.9Data Integration and Real-Time Analysis
  50. 5.20Success Stories: Implementing Monte Carlo in Naval Projects
  51. 6.2Practical Application of Risk Analysis: Methodologies
  52. 6.2Implementing Monte Carlo in Comprehensive Planning
  53. 6.3Case Studies: Risk Analysis in Specific Projects
  54. 6.4Developing Risk Models for Planning
  55. 6.5Risk Mitigation and Response Techniques
  56. 6.6Sensitivity Analysis and Multiple Scenarios
  57. 6.7Risk Management in the Project Life Cycle
  58. 6.8Evidence-Based Decision Making
  59. 6.9Implementing Tools and Software
  60. 6.20Best Practices in Risk Management
  61. 7.2Risk-Driven Master Planning
  62. 7.2Integrating Monte Carlo into Long-Term Planning Timeframe
  63. 7.3Risk Analysis in Resource Allocation
  64. 7.4Development of Contingency and Resilience Plans
  65. 7.5Uncertainty Management in Decision Making
  66. 7.6Use of Historical Data to Improve Planning
  67. 7.7Real-Time Risk Monitoring and Control
  68. 7.8Implementation of KPIs for Risk Management
  69. 7.9Optimization of Strategic Planning
  70. 7.20Case Studies: Master Planning with Risk Analysis
  71. 8.2Integration of Risk Analysis into Decision Making
  72. 8.2Application of Monte Carlo in Project Evaluation
  73. 8.3Sensitivity Analysis and Scenario Evaluation
  74. 8.4Evidence-Based Decision Making
  75. 8.5Development of Risk Models for Decision Making
  76. 8.6Risk Management in the Project Life Cycle
  77. 8.7Implementation of Tools and Software
  78. 8.8Best Practices in Risk Management Risks
  79. 8.9Risk Communication and Reporting
  80. 8.20Success Stories: Integration into Decision-Making
  1. 3.3Introduction to Planning Optimization through Monte Carlo Simulation
  2. 3.2Risk Identification and Categorization in Planning
  3. 3.3Scenario Modeling and Uncertain Variables
  4. 3.4Monte Carlo Simulation: Fundamentals and Application
  5. 3.5Resource Optimization and Task Allocation
  6. 3.6Sensitivity Analysis and "What-If" Scenarios
  7. 3.7Decision-Making Based on Simulation Results
  8. 3.8Tools and Software for Monte Carlo Simulation
  9. 3.9Case Studies and Examples in Naval Planning
  10. 3.30Strategies for Continuous Improvement and Adaptability
  1. 4.4Fundamentals of Risk Analysis and Monte Carlo Simulation
  2. 4.2Risk Identification and Assessment in Naval Projects
  3. 4.3Risk Modeling with Monte Carlo Simulation
  4. 4.4Application of Monte Carlo in Naval Task Planning
  5. 4.5Sensitivity Analysis and Scenarios in Planning
  6. 4.6Tools and Software for Risk Analysis
  7. 4.7Integrating Risk Analysis into Decision-Making
  8. 4.8Case Studies: Real-World Applications in the Naval Sector
  9. 4.9Risk Mitigation and Response Strategies
  10. 4.40Risk Monitoring and Control in Project Execution
  1. 5.5Introduction to Risk Analysis in Naval Planning
  2. 5.5Fundamentals of Monte Carlo Simulation
  3. 5.3Risk Identification and Categorization
  4. 5.4Modeling Tools and Techniques
  5. 5.5Practical Application: Naval Case Study
  6. 5.6Sensitivity Analysis and Scenarios
  7. 5.7Interpretation of Results and Decision Making
  8. 5.8Integration with Strategic Planning
  9. 5.5Integration of Monte Carlo in Naval Project Management
  10. 5.5Definition of Objectives and Scope
  11. 5.3Data Collection and Analysis
  12. 5.4Risk Model Development
  13. 5.5Simulation and Evaluation of Results
  14. 5.6Risk Management: Mitigation and Contingency
  15. 5.7Plan Monitoring and Control
  16. 5.8Adaptation and Continuous Improvement
  17. 3.5Resource and Budget Optimization
  18. 3.5Simulation for Task Scheduling
  19. 3.3Supply Chain Analysis
  20. 3.4Evaluation of the Resource Availability
  21. 3.5What-If Scenario Design
  22. 3.6Data-Driven Decision Making
  23. 3.7Bottleneck Identification
  24. 3.8Mitigation Strategies for Optimization
  25. 4.5Identification and Evaluation of Specific Risks
  26. 4.5Complex Risk Modeling
  27. 4.3Advanced Monte Carlo Simulation Techniques
  28. 4.4Results Analysis and Report Creation
  29. 4.5Impact and Probability Assessment
  30. 4.6Mitigation Strategies and Contingency Plans
  31. 4.7Scenario-Based Decision Making
  32. 4.8Post-Implementation Evaluation
  33. 5.5Design and Development of Advanced Monte Carlo Models
  34. 5.5Integration with Specialized Software
  35. 5.3Selection of Probability Distributions
  36. 5.4Model Validation and Verification
  37. 5.5​​Results Analysis and Reporting
  38. 5.6Sensitivity Analysis and Scenario Analysis
  39. 5.7Implementation Mitigation Strategies
  40. 5.8Risk Management in Dynamic Environments
  41. 5.9Adapting to New Risks and Challenges
  42. 5.50Continuous Improvement and Model Updating
  43. 6.5Practical Application in Naval Case Studies
  44. 6.5Risk Analysis in Equipment Acquisition
  45. 6.3Risk Assessment in Naval Operations
  46. 6.4Maintenance and Repair Planning
  47. 6.5Risk Management in Naval Logistics
  48. 6.6Financial and Budgetary Risk Analysis
  49. 6.7Strategic Decision Making
  50. 6.8Crisis Management and Contingency Plans
  51. 7.5Development of the Master Plan
  52. 7.5Integration of Risk Analysis into Planning
  53. 7.3Definition of Objectives and Goals
  54. 7.4Strategic Risk Analysis
  55. 7.5Implementation of Mitigation Strategies
  56. 7.6Monitoring and Control of the Master Plan
  57. 7.7Communication and Presentation of Results
  58. 7.8Adaptation and Continuous Improvement of Planning
  59. 8.5Integration of Risk Analysis into Decision Making
  60. 8.5Use of Data and Analysis for Informed Decision Making
  61. 8.3Evaluation of Different Scenarios and Outcomes
  62. 8.4Identification of Key Risks
  63. 8.5Mitigation Strategies and Contingency Plans
  64. 8.6Communication and Presentation of Results
  65. 8.7Impact and Probability Assessment
  66. 8.8Strategic Decision Making
  1. 6.6Fundamentals of Risk Analysis in Strategic Naval Planning
  2. 6.2Introduction to the Monte Carlo Method and its Application in Naval Scenarios
  3. 6.3Identification and Evaluation of Risks in Naval Operations
  4. 6.4Development of Risk Models for Monte Carlo Simulation
  5. 6.5Interpretation of Results and Strategic Decision Making
  6. 2.6Implementation of Risk Analysis in Naval Projects
  7. 2.2Integration of Monte Carlo in Maritime Project Management
  8. 2.3Tools and Software for Risk Analysis and Simulation
  9. 2.4Risk Monitoring and Control During Project Execution
  10. 2.5Uncertainty Management in Naval Planning and Management
  11. 3.6Optimization Techniques using Monte Carlo Simulation
  12. 3.2Sensitivity Analysis and Scenarios in Naval Planning
  13. 3.3Identification of Critical Success Factors and Bottlenecks
  14. 3.4Optimization of Resources and Budgets Using Monte Carlo Carlo
  15. 3.5Strategies for Risk Mitigation and Performance Improvement
  16. 4.6Advanced Risk Assessment Methods in the Naval Sector
  17. 4.2Application of Monte Carlo Simulation in Different Scenarios
  18. 4.3Impact and Probability Analysis of Risks in Naval Operations
  19. 4.4Design of Contingency Plans Based on Simulation
  20. 4.5Validation and Verification of Risk Models in Planning
  21. 5.6Implementation of Monte Carlo for Reliable Planning
  22. 5.2Development of Risk Models for Decision Making
  23. 5.3Selection and Application of Simulation Tools
  24. 5.4Design of Risk Mitigation Strategies
  25. 5.5Risk Control and Continuous Improvement in Naval Planning
  26. 6.6Practical Applications of Risk Analysis in Naval Design
  27. 6.2Application of the Monte Carlo Method in Naval Logistics
  28. 6.3Scenario Simulation for Tactical Decision Making
  29. 6.4Evaluation of Risks in Maritime Transport Operations
  30. 6.5Risk Analysis in Naval Supply Chain Management
  31. 6.6Case Studies: Practical Application of Risk Analysis and Monte Carlo
  32. 7.6Risk-Driven Master Planning
  33. 7.2Integrating Monte Carlo into Resource Planning
  34. 7.3Developing Probabilistic Schedules and Budgets
  35. 7.4Evaluating the Feasibility of Naval Projects
  36. 7.5Risk Management and Change Control in Master Planning
  37. 8.6Integrating Risk Analysis into Decision-Making
  38. 8.2Using Monte Carlo to Evaluate Strategic Options
  39. 8.3Cost-Benefit Analysis with Risk Inclusion
  40. 8.4Communicating Results and Data-Driven Decision-Making
  41. 8.5Developing a Risk Management Culture in the Organization
  1. 7.7Fundamentals of Risk Analysis: Identification and Assessment
  2. 7.2Introduction to Monte Carlo Simulation: Principles and Applications
  3. 7.3Risk Modeling: Variables, Distributions, and Parameters
  4. 7.4Tools for Risk Analysis and Monte Carlo
  5. 7.7Application in Strategic Planning: Case Studies
  6. 7.6Interpretation of Results and Data-Driven Decision Making
  7. 7.7Sensitivity and Scenario Analysis: Identification of Key Factors
  8. 7.8Risk Management: Mitigation and Response Strategies
  9. 2.7Integrating Risk Analysis into the Planning Process
  10. 2.2Implementing Monte Carlo Simulation: Steps and Methodology
  11. 2.3Designing Simulation Models: Software and Advanced Techniques
  12. 2.4Sensitivity Analysis and Determining Critical Factors
  13. 2.7Validation and Verification of Risk Models
  14. 2.6Application in Project and Operations Management
  15. 2.7Monitoring and Risk Management: Key Performance Indicators
  16. 2.8Continuous Improvement: Feedback and Process Optimization
  17. 3.7Introduction to Optimization: Concepts and Methodologies
  18. 3.2Optimization Techniques Applied to Risk Analysis
  19. 3.3Design of Experiments and Monte Carlo Simulation
  20. 3.4Cost-Benefit Analysis and Decision Making
  21. 3.7Resource Optimization and Task Assignment
  22. 3.6Time Optimization and Activity Scheduling
  23. 3.7Supply Chain and Logistics Optimization
  24. 3.8Results Analysis and Strategic Recommendations
  25. 4.7Advanced Methodologies for Risk Assessment
  26. 4.2Monte Carlo Simulation Models for Complex Scenarios
  27. 4.3Data Analysis Techniques and Results Visualization
  28. 4.4Incorporation of Historical Data and Market Trends
  29. 4.7Impact Assessment: Sensitivity Analysis and Scenarios
  30. 4.6Planning Contingency: Development of Action Plans
  31. 4.7Strategy Analysis: Comparison and Evaluation
  32. 4.8Reporting and Effective Risk Communication
  33. 7.7Selection of Software and Advanced Tools
  34. 7.2Development of Customized Simulation Models
  35. 7.3Implementation of Optimization Techniques in Planning
  36. 7.4Integration with Project Management Systems
  37. 7.7Automation of Processes and Workflows
  38. 7.6Training and Development of the Planning Team
  39. 7.7Creation of Customized Dashboards and Reports
  40. 7.8Evaluation of Results and Continuous Process Improvement
  41. 6.7Real-World Case Studies and Practical Examples
  42. 6.2Application in Different Types of Projects and Operations
  43. 6.3Design of Risk Models and Monte Carlo Simulation
  44. 6.4Data Analysis and Interpretation of Results
  45. 6.7Implementation of Risk Mitigation Strategies
  46. 6.6Decision-Making Based on Evidence
  47. 6.7Project Management and Progress Control
  48. 6.8Results Presentation and Effective Communication
  49. 7.7Master Planning Overview
  50. 7.2Integrating Risk Analysis into Master Planning
  51. 7.3Developing Simulation Models for Planning
  52. 7.4Sensitivity Analysis and Scenario Evaluation
  53. 7.7Optimizing Resource Allocation
  54. 7.6Developing Contingency Plans
  55. 7.7Monitoring and Controlling the Master Plan
  56. 7.8Reviewing and Updating the Plan Based on Risks
  57. 8.7Introduction to Risk Integration and Monte Carlo
  58. 8.2Methodology for Integration in Planning
  59. 8.3Designing Integrated Risk and Simulation Models
  60. 8.4Scenario Analysis and Impact Assessment
  61. 8.7Decision Making in Uncertain Environments
  62. 8.6Integrated Project and Operations Management
  63. 8.7Risk Communication and Decision Making
  64. 8.8Improvement Continuous Improvement and Adaptation to Change
  1. 8.8Introduction to Risk Analysis in the Naval Sector
  2. 8.8Fundamentals of Monte Carlo Simulation
  3. 8.3Identification and Classification of Naval Risks
  4. 8.4Probability and Statistics Applied to Risk
  5. 8.5Tools and Software for Risk Analysis
  6. 8.8Integration of Risk Analysis into Naval Planning
  7. 8.8Application of Monte Carlo in Naval Project Management
  8. 8.3Scenario Modeling and Risk Simulation
  9. 8.4Uncertainty Management in Planning
  10. 8.5Risk Monitoring and Control in Naval Operations
  11. 3.8Optimization Strategies Through Simulation
  12. 3.8Sensitivity Analysis and Scenarios
  13. 3.3Resource and Budget Optimization
  14. 3.4Improvement of Operational Efficiency
  15. 3.5Decision-Making Based on Simulated Results
  16. 4.8Comprehensive Risk Assessment in Planning
  17. 4.8Design of Advanced Monte Carlo Simulations
  18. 4.3Risk Impact and Probability Analysis
  19. 4.4Development of Contingency Plans
  20. 4.5Evaluation of Strategy Effectiveness
  21. 5.8Expert Implementation of Monte Carlo Simulation
  22. 5.8Model Selection and Customization
  23. 5.3Simulation Validation and Verification
  24. 5.4Results Analysis and Reporting
  25. 5.5Risk Management in Complex Environments
  26. 6.8Practical Cases of Risk Analysis in Planning
  27. 6.8Application in Different Naval Areas
  28. 6.3Development of Customized Simulation Models
  29. 6.4Integration with Planning Tools
  30. 6.5Best Practices and Lessons Learned
  31. 7.8Master Planning and its Relationship to Risk Analysis
  32. 7.8Incorporation of Simulation Results into Planning
  33. 7.3Long-Term Risk Management
  34. 7.4Informed Strategic Decision Making
  35. 7.5Adaptation to Changes and Unexpected Scenarios
  36. 8.8Integration of Risk Analysis into Decision Making
  37. 8.8Use of Monte Carlo Simulation in Strategic Decisions
  38. 8.3Evaluation of Different Options and Scenarios
  39. 8.4Effective Communication of Analysis Results
  40. 8.5Implementation of a Comprehensive Risk Management System
  1. 9.9Fundamentals of Risk Analysis in Naval Planning
  2. 9.9Introduction to Monte Carlo Simulation
  3. 9.3Identification and Evaluation of Key Risks
  4. 9.4Scenario Design and Initial Modeling
  5. 9.5Practical Application in Case Studies
  6. 9.9Integration of Risk Analysis into Planning
  7. 9.9Implementation of Monte Carlo in Naval Project Management
  8. 9.3Development of Risk Models for Decision Making
  9. 9.4Risk Monitoring and Control during Execution
  10. 9.5Tools and Software for Implementation
  11. 3.9Optimization of Resource Allocation
  12. 3.9Sensitivity Analysis and "What-If" Scenarios
  13. 3.3Impact Assessment on Costs and Schedules
  14. 3.4Identification of Critical Points and Bottlenecks
  15. 3.5Risk Mitigation Strategies
  16. 4.9Risk Assessment Methodology
  17. 4.9Advanced Monte Carlo Simulation Techniques Carlo
  18. 4.3Results Analysis and Data Interpretation
  19. 4.4Model Validation and Calibration
  20. 4.5Applications in Tactical and Strategic Planning
  21. 5.9Design and Implementation of a Risk Management Process
  22. 5.9Selection and Application of Specialized Software
  23. 5.3Creation of Reports and Detailed Documentation
  24. 5.4Communication and Collaboration in Risk Management
  25. 5.5Best Practices in Naval Planning
  26. 6.9Case Studies of Comprehensive Planning
  27. 6.9Application in Different Phases of the Project Life Cycle
  28. 6.3Integration with Other Planning Tools
  29. 6.4Cost-Benefit and Profitability Analysis
  30. 6.5Data-Driven Decision Making
  31. 7.9Development of a Master Plan with Risk Analysis
  32. 7.9Integration of Monte Carlo Simulation into the Master Plan
  33. 7.3Monitoring and Updating the Plan
  34. 7.4Impact Analysis of Changes in the Plan
  35. 7.5Performance and Control Reports
  36. 8.9Integrating Risk Analysis into Decision Making
  37. 8.9The Role of Monte Carlo in Strategy Selection
  38. 8.3Risk and Opportunity Assessment
  39. 8.4Communicating Risks to Stakeholders
  40. 8.5Informed and Resilient Decision Making
  41. 8.5
  1. 1.1Mastering Risk Analysis and Monte Carlo Simulation in Strategic Planning
  2. 1.2Risk Analysis and Monte Carlo Simulation Methodology
  3. 1.3Scenario Modeling and Critical Variables
  4. 1.4Implementing Monte Carlo Simulation
  5. 1.5Interpreting Results and Decision Making
  6. 1.6Tools and Software for Risk Analysis
  7. 1.7Practical Applications in Naval Planning
  8. 1.8Case Studies: Strategic Planning
  9. 1.9Risk and Opportunity Assessment
  10. 1.10Mitigation and Contingency Strategies
Methodology, software & labs

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.
Accreditable laboratories(EN ISO/IEC 17025) with rotor bench, EMC/Lightning pre-compliance, HIL/SIL, vibrations/acoustics.
Evidence-oriented Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry Mentored:teachers with experience in training, , eVTOL/UAM and flight test.
Flexible modality(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, cyber-OT, DIH and compliance as pillars.
Career opportunities

Where this takes you

**Risk Analyst** (Projects, Finance)**Risk Analyst** (Planning, Projects)**Risk Analyst** (Planning, Projects, Finance)**Risk and Planning Analyst** (Projects, Finance, Monte Carlo)**Risk and Planning Analyst** (Monte Carlo, Projects)**Risk and Planning Analyst** (Monte Carlo, Projects)
Admissions & scholarships

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.

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FAQ

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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