Dr. Marina AlcoverAcademic director focused on measurable results and operational excellence in maritime education. Integrates IMO/STCW regulations and ISO 21001/9001 f
Course · 300 h · 5 modules
Artificial intelligence in navigation course
This course prepares you to lead the technological revolution in the maritime sector. Learn to implement and manage intelligent systems that optimize the safety, efficiency, and sustainability of naval operations. Master the…
Duration300 h
FormatOnline
Starts7 December
Places20 / 20
Prior knowledge
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Programme overview
What is the Artificial intelligence in navigation course?
The Artificial Intelligence in Navigation Course
This course prepares you to lead the technological revolution in the maritime sector. Learn to implement and manage intelligent systems that optimize the safety, efficiency, and sustainability of naval operations. Master the techniques of machine learning, computer vision, and predictive analytics applied to autonomous navigation, fleet management, and risk prediction. This course will allow you to transform data into strategic decisions and become a highly sought-after professional in the industry.
Differential Advantages
- Practical Applications: Development of real-world projects through simulation and case study analysis.
- Industry Experts: Training delivered by professionals with experience in AI and navigation.
- Cutting-Edge Tools: Access to leading artificial intelligence software and platforms.
- Networking: Connection with a community of professionals and innovative companies.
- Certification: Obtain a certificate that validates your knowledge and skills in AI applied to navigation.
Programme type
Course
Study mode
Online
Duration
300 hours
Modules
5
Start date
08-12-2026
Programme highlights
- AI Fundamentals: Discover the basic principles of artificial intelligence and its application in modern navigation.
- Smart Sensors: Learn how to use and understand data from advanced sensors for safer and more efficient navigation.
- Navigation Algorithms: Master the key algorithms that allow AI systems to plan optimal routes and avoid obstacles in real time.
- Automation and Safety: Explore how AI can automate navigation tasks, improve maritime safety, and reduce the risk of human error.
- Case Studies: Analyze real-world examples of AI implementation on vessels and learn from industry experiences.
- Boost your navigation career with the latest Artificial Intelligence technologies.
Curriculum
Programme Structure
The programme is structured in 5 modules, listed below in order of study.
01
Fundamentals of artificial intelligence applied to navigation, autonomous systems and assisted decision-making in maritime environments
- Artificial intelligence concept and its evolution in maritime, river and nautical navigation systems of new generation
- Differences between automation, advanced analytics, machine learning and intelligent systems applied to the navigation domain
- Functional architecture of an AI solution for navigation: sensors, data, models, inference, interface and decision support
- Critical variables of the navigational environment susceptible to AI treatment: traffic, meteorology, defeat, risk, consumption and behaviour of the boat
- Relationship between artificial intelligence, operational safety, route efficiency, situational awareness and reduction of human error
02
Data, sensors and intelligent perception systems for artificial intelligence based navigation
- Data sources for AI in navigation: radar, AIS, GNSS, cameras, echo sounder, meteorology, digital cartography and embarked sensors
- Navigational data quality, consistency and traceability: cleaning, synchronisation, labelling and preparation for model training
- Multimodal sensory and environment perception: obstacle detection, maritime traffic, sea conditions and spatial references
- Data fusion for intelligent navigation: integration of heterogeneous signals and construction of a unified operational vision
- Anomaly detection and pattern recognition in navigation variables using machine learning techniques
03
Machine learning models and AI algorithms for prediction, optimisation and navigation assistance
- Fundamentals of supervised, unsupervised and reinforced machine learning applied to navigation problems
- Predictive models for meteorology, traffic, consumption, collision risk and dynamic behaviour of the boat
- Route and defeat optimisation algorithms with AI: distance, security, time, consumption and weather-oceanic conditions
- Manoeuvre recommendation systems and tactical assistance to decision making in coastal, oceanic and port navigation
- Relevant event classification and detection models: intrusion, route diversion, irregular navigation and anomalous operating conditions
04
Integration of artificial intelligence with navigation systems, digital bridge and maritime control platforms
- AI integration with ECDIS, AIS, radar, autopilot, fleet management systems and integrated bridge consoles
- Design of smart interfaces for assisted navigation: Alerts display, recommendations, priorities and operator cognitive support
- Advanced Situational Awareness AI: Contact Correlation, Path Prediction, and Dynamic Assessment of the Maritime Environment
- Application of artificial intelligence to autonomous and semi-autonomous navigation systems in manned and unmanned boats
- Real-time monitoring, edge computing and on-board processing for fast decisions in changing navigation conditions
05
Capstone Project for artificial intelligence design and application for a real or simulated navigation case
- Definition of the case study: type of boat, mission profile, navigational problem and improvement objectives through AI
- Selection of relevant data, sensors and variables to build an intelligent solution adapted to the proposed scenario
- AI model or system design: functional architecture, inference logic, operational integration and performance criteria
- Development of the flow of use in navigation: data capture, processing, generation of alerts or recommendations and human validation
- Technical and operational evaluation of the proposal: expected precision, limitations, risks, practical utility and scalability of the solution
Workload
Study Time and Workload
300 hours of study, online and at your own pace. Move the slider to the hours a week you can really put in.
Hours a week8
Weeks to finish—
You finish around—
Who it is for
Bridge officers, captains, and fleet management personnel looking to optimize routes, reduce fuel costs, and improve safety through AI.Naval engineers and software developers interested in implementing AI algorithms in maritime navigation and control systems.Data analysts and maritime consultants who want to understand the potential of AI for strategic decision-making in the maritime industry.
Faculty
Academic direction and faculty
The teaching team at Navalis: working professionals who deliver and oversee the institute's programmes.
Eng. Diego Cifuentes
Cap. Javier Abaroa (MCA)
Dr. Pau Ferrer
Dr. Nuria Llobregat
Eng. Javier Bañuls
Eng. Sofía Marquina
Eng. Tomás Riera
Verified reviews
Student Reviews
Reviews collected and verified by Opynio, not written by us.
Outcomes
Learning Outcomes
- 01Dynamically adapt routes
- 02Optimize fuel consumption
- 03Managing autonomous maritime traffic
- 04Predicting and avoiding collisions
- 05Improve navigation accuracy in adverse conditions
- 06Automate critical decision-making
Careers
Career Opportunities
01Autonomous Navigation Software Developer: Design, development, and testing of AI algorithms for navigation systems.
02Marine Robotics Engineer: Integration of AI into autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs).
03Navigation Data Analyst: Processing and analysis of large navigation datasets to optimize routes and predict risks.
04AI Consultant for the Maritime Industry: Advising shipping companies and ports on the implementation of AI solutions.
05AI Researcher Applied to Navigation: Development of new AI techniques to improve navigation safety and efficiency.
06AI Navigation Simulation Specialist: Creation of realistic simulation environments for the training and testing of autonomous navigation systems.
07Autonomous Navigation Systems Cybersecurity Expert: Protecting navigation systems against cyberattacks.
08AI Project Manager in Navigation: Leading and coordinating AI development and implementation projects in the maritime industry.
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Questions
Entry Requirements
Improve safety and efficiency.
Yes. The itinerary includes ECDIS/Radar-ARPA/BRM with harbor, ocean, fog, storm, and SAR scenarios.
Online with live sessions; hybrid option for simulator/practical placements through agreements.
Optimizing navigation routes in real time by considering variables such as weather, ocean currents and traffic, minimizing travel time and therefore fuel consumption.
Recommended functional SMCP. We offer support materials for standard phraseology.
Yes, with a relevant degree or experience in maritime/port operations. The admissions interview will confirm suitability.
Optional (3–6 months) through Companies & Collaborations and the Alumni Network.
Simulator practice (rubrics), defeat plans, SOPs, checklists, micro-tests and applied TFM.
A degree from Navalis Magna Institute + operational portfolio (tracks, SOPs, reports and KPIs) useful for audits and employment.
Online admissions
Admissions Process
No waiting for a phone call. If your documents are complete, you can pay in the same session.
Entry requirements
Academic/Professional Profile:Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a related field; or demonstrable professional experience in software development, robotics, or AI-related fields.Technical Skills:Solid foundation in programming (Python preferred), linear algebra, calculus, probability, and statistics. Basic knowledge of machine learning and deep learning is valued.Language proficiency:Technical English (reading and comprehension) for understanding documentation, papers, and online resources.Documentation:Updated CV,
Questions?
Frequently Asked Questions
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