AI-powered traffic control course at UAM
About our
The Air Traffic Control with AI in UAM course explores the use of Artificial Intelligence (AI) to optimize urban air mobility (UAM) control. It focuses on the application of machine learning algorithms and data analysis for route planning, congestion management, and safety improvement in the UAM environment, considering aspects such as traffic modeling, scenario simulation, and integration with air traffic management (ATM) systems. It addresses the development of AI-based solutions for anomaly detection and automated decision-making, which are fundamental for the safe and efficient operation of unmanned aerial vehicles (UAVs) and urban air mobility (UAM) aircraft.
This course provides practical knowledge in the design of intelligent air traffic control systems, using simulation tools and data analysis to evaluate the performance and feasibility of proposed solutions. It focuses on the application of AI in UAM, including route optimization, airspace management, and flight planning. This course prepares participants for roles such as AI air traffic control specialists, UAM data analysts, UAM systems engineers, and UAM software developers, driving the advancement of urban air mobility.
This course provides practical knowledge in the design of intelligent air traffic control systems, using simulation tools and data analysis to evaluate the performance and feasibility of proposed solutions.
AI-powered traffic control course at UAM
- Format: Hybrid
- Duration: 3 months
- Hours: 300 H
- Language: English / Spanish
- Registration date: 23-10-2026
- Start date: 12-12-2026
- Available places: 3
550 $
Competencies and results
What you will learn
1. Mastery of AI in Naval Traffic Control: A UAM Course
- Identification and analysis of maritime traffic patterns using artificial intelligence algorithms.
- Implementation of AI systems for collision prediction and real-time route optimization.
- Development of skills in using AI tools for traffic data analysis and strategic decision-making.
- Understanding maritime legislation and its integration with AI systems for regulatory compliance and safety.
- Application of machine learning techniques for the continuous improvement of maritime traffic control.
2. Optimization of Naval Traffic with AI: UAM Course
- Master predictive analysis of maritime traffic using Artificial Intelligence.
- Implement AI models to optimize shipping routes, considering variables such as weather, congestion, and fuel efficiency.
- Use AI tools for risk management and real-time decision-making in naval operations.
- Analyze historical traffic data and simulate future scenarios to improve planning and safety.
- Learn about the latest trends in AI applied to the maritime sector and its impact on sustainability and operational efficiency.
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. Implementation of AI for Advanced Naval Traffic Management: UAM Course
Here is the requested content:
4. Implementation of AI for Advanced Maritime Traffic Management: UAM Course
Understand the fundamentals of AI and machine learning applied to maritime navigation.
Explore the use of AI algorithms to optimize navigation routes and reduce fuel consumption.
Learn to use AI for maritime traffic prediction and management, including collision detection and congestion management.
Analyze the use of AI systems for monitoring and predictive maintenance of ships and equipment.
Study the applications of AI in maritime safety, including threat detection and emergency response.
Become familiar with the most widely used AI tools and platforms in the maritime industry.
Develop practical skills in the implementation and management of AI solutions for maritime traffic management.
5. Analysis and Control of Naval Traffic with AI: UAM Course
- Understand the fundamentals of Artificial Intelligence (AI) applied to maritime traffic management.
- Use AI tools for the detection and prediction of maritime traffic patterns.
- Analyze maritime traffic data to identify risks and optimize operational efficiency.
- Apply AI algorithms for collision management and accident prevention at sea.
- Master the use of intelligent systems for real-time maritime traffic monitoring and control.
- Evaluate and mitigate risks associated with maritime traffic, including security and environmental threats.
- Develop strategies for route optimization and fleet management using AI.
- Integrate AI with maritime navigation and communication systems for comprehensive maritime traffic management.
- Analyze case studies and practical examples of AI applications in the maritime sector.
- Apply the knowledge acquired to solve real-world problems related to maritime traffic.
6. UAM Course: AI for Efficiency and Safety in Naval Traffic Control
6. UAM Course: AI for Efficiency and Safety in Maritime Traffic Control
Understand the fundamentals of Artificial Intelligence (AI) and its application in the naval field.
Analyze maritime traffic data to identify patterns and anomalies.
Use AI algorithms to optimize routes and reduce congestion in navigation areas.
Apply AI techniques to predict collisions and improve maritime safety.
Implement AI systems for the efficient management of ports and terminals.
Explore the use of AI in threat detection and emergency response at sea.
Evaluate the impact of AI on the operational efficiency and sustainability of maritime transport.
Learn about the ethical and legal considerations related to the use of AI in the naval sector.
Develop practical skills in the use of AI tools and platforms relevant to maritime traffic control.
Study case studies and real-life examples of the successful application of AI in the maritime sector.
Who this program is for:
AI-powered traffic control course at UAM
- Graduates in Aerospace Engineering, Mechanical Engineering, Industrial Engineering, Automation Engineering, or related fields.
- Professionals from OEM rotorcraft/eVTOL, MRO, consulting, technology centers.
- Flight Testing, certification, avionics, control, and dynamics seeking specialization.
- Regulators/authorities and UAM/eVTOL professionals requiring compliance skills.
Recommended qualifications: foundation in aerodynamics, 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.
Module 1 — Introduction to AI in Maritime Traffic
1.1 AI Fundamentals and its Application to Maritime Traffic
1.2 Introduction to Maritime Traffic Management (MTM) Systems
1.3 Data Collection and Analysis in the Naval Environment
1.4 AI Algorithms Relevant to Traffic Control
1.5 Machine Learning and Neural Networks in the Maritime Context
1.6 Ethics and Legal Considerations in the Use of Naval AI
1.7 Introduction to Cybersecurity in AI Systems for Maritime Traffic
1.8 Impact of AI on Maritime Efficiency and Safety
1.9 Case Studies: Current Applications of AI in Maritime Traffic
1.10 Future Trends and Challenges of AI in Maritime Traffic Control
2.2 Relevant International and National Maritime Legislation
2.2 International Conventions and Agreements on Maritime Safety
2.3 Regulatory Framework for Maritime Traffic: Functions and Responsibilities
2.4 Fundamental Principles of Maritime Safety and Safe Navigation
2.5 Roles and Responsibilities of Maritime and Port Authorities
2.6 Regulations on Collision Prevention and Maritime Signals
2.7 Regulations on the Protection of the Marine Environment
2.8 The SOLAS Convention and its Impact on Shipping Traffic Control
2.9 International Ship and Port Facility Security (ISPS) Legislation
2.20 Ethics and Responsibility in Shipping Traffic Control
3.3 Fundamentals of Maritime Traffic and its Evolution
3.2 Introduction to Artificial Intelligence: Key Concepts
3.3 AI and its Application in Different Sectors: An Overview
3.4 The Role of AI in the Transformation of Maritime Traffic Control
3.5 Advantages and Challenges of AI in the Maritime Sector
3.6 Ethics and Responsibility in the Use of AI in the Maritime Sector
3.7 Key AI Technologies Relevant to Traffic Control
3.8 Data Sources and their Importance for AI in Maritime Traffic
3.9 AI Tools and Platforms for Naval Data Analysis
3.30 Case Studies: Initial Applications of AI in Maritime Traffic Control
4.4 Fundamentals of Maritime Traffic: Principles and Regulations
4.2 Introduction to Artificial Intelligence: Key Concepts
4.3 AI in the Maritime Context: Current and Future Applications
4.4 The Role of AI in Maritime Traffic Control: Overview
4.5 Data in Maritime Traffic: Sources, Types, and Management
4.6 Ethics and Legal Considerations of AI at Sea
4.7 Challenges and Opportunities of AI in the Maritime Sector
4.8 Relevant AI Tools and Technologies
4.9 Case Study: Examples of AI Applications in Maritime Traffic
4.40 Future Trends: The Future of Maritime Traffic Control with AI
5.5 Principles of Maritime Traffic: Regulation and Structure
5.5 Maritime Navigation Systems and Their Operation
5.3 Introduction to Artificial Intelligence: Key Concepts and Applications
5.4 Machine Learning and Neural Networks in a Naval Context
5.5 Data and Data Sources Relevant to Maritime Traffic
5.6 AI Tools and Technologies Applicable to Traffic Control
5.7 Ethics and Legal Considerations in the Use of AI at Sea
5.8 Introduction to AI Algorithms for Naval Data Analysis
5.9 Initial Case Studies on AI and Maritime Traffic
5.50 Introduction to Security and Data Protection in Naval Environments
6.6 Introduction to Artificial Intelligence (AI)
6.2 Fundamentals of Naval Traffic Control
6.3 Integrating AI into Control Systems
6.4 AI Algorithms Applicable to Naval Traffic
6.5 Data Collection and Analysis in the Naval Environment
6.6 Ethics and Legal Considerations in the Use of AI
6.7 AI System Architecture for Control
6.8 Neural Networks and Machine Learning in Naval Traffic
6.9 Case Studies: Current AI Applications in the Naval Sector
6.60 Future Challenges and Opportunities
- 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”).