Course in Ethics in Explainable AI in Military Simulation
Online 300-hour course in Ethics in Explainable AI in Military Simulation. 6 modules covering Regulation (EU) 2024/1689 (AI Act, transparency and human oversight), IEEE 7001 (transparency of autonomous systems) and SHAP. Personal tutor assigned and enrolment open.
Course in Ethics in Explainable AI in Military Simulation — studying from Canada
Canada's defence sector is centred on procurement and sustainment through the Department of National Defence and Defence Research and Development Canada. Industrial activity spans land vehicles, naval systems, avionics and electronics, with firms in Ontario, Québec, Nova Scotia and British Columbia. Companies such as General Dynamics Land Systems Canada and Lockheed Martin Canada are notable employers, alongside a broad base of small and medium suppliers. Engineers work on systems integration, vehicle protection, logistics and sustainment, operating within strict security and export control frameworks.
Fees for Canada: C$1,240 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Which Canadian bodies or processes govern defence engineering recognition?
Defence engineering in Canada often involves government procurement and security clearances, and engineers typically hold provincial Professional Engineer licences where a title is required. SEIUM's qualifications are private and not official state degrees or accredited by a national body, so they do not confer licensing or clearance. Recognition is for employers or the relevant body to decide, so verify this first.
Would Canadian defence or land systems employers accept this training?
Canadian defence employers and contractors generally rely on security clearance, licensing and demonstrated experience. A private qualification may support your application, but it is unlikely to replace those requirements, and its acceptance is up to each employer. A SEIUM final project can help show applied skill, so discuss expectations with prospective employers early.
Can I study remotely while working, and what are the costs and language demands?
Yes, the programmes are fully online, so you can study from Canada or elsewhere without a student visa, and fit sessions around work. Specialist courses are 300 hours, postgraduate diplomas 800 and master's 1,900. Teaching is in English, supported by an assigned technical tutor. Fees are payable in instalments, and employer sponsorship may be available.
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What you will be able to do
Explain the concepts and techniques of explainability in AI.
Analyse the use of intelligent agents in military simulation.
Apply explanation techniques to decision-making agents.
Evaluate the calibration of user trust in AI.
Identify transparency and human oversight requirements.
Assign responsibilities in the design of AI-based simulations.
Develop a simulation with explainable components.
Who it's for
- Researcher in explainable AI who wants to specialise in Ethics in Explainable AI in Military Simulation.
- Simulation engineer who wants to specialise in Ethics in Explainable AI in Military Simulation.
- Human factors specialist who wants to specialise in Ethics in Explainable AI in Military Simulation.
- Reinforcement learning engineer who wants to specialise in Ethics in Explainable AI in Military Simulation.
- AI verification analyst who wants to specialise in Ethics in Explainable AI in Military Simulation.
- Training environment designer who wants to specialise in Ethics in Explainable AI in Military Simulation.
- Graduates in engineering or sciences looking to enter simulation and training.
What you'll work with
- Regulation (EU) 2024/1689 (AI Act, transparency and human oversight)
- IEEE 7001 (transparency of autonomous systems)
- ISO/IEC 22989 (AI concepts and terminology)
- STANAG 4603 (HLA simulation architectures in NATO)
- IEEE 1516 (High Level Architecture)
- ISO/IEC TR 29119-11 (testing of AI systems)
- NATO Principles for the Responsible Use of AI (2021)
6 modules · 300 h
1.1Interpretability versus explainability1.2Intrinsically interpretable models1.3Post hoc explanations: LIME and SHAP1.4Saliency maps and Grad-CAM1.5Counterfactual explanations1.6DARPA XAI programme1.7ISO/IEC TR 24028 and trustworthiness1.8Recipients of the explanation1.9Limits of explanations1.10Case study: comparing explanations of the same model
2.1Constructive, virtual and live simulation2.2Computer-generated forces and AI agents2.3Reinforcement learning in wargames2.4Simulation for training and for planning2.5Intelligent adversarial agents2.6HLA and DIS interoperability2.7Evaluation of AI agents2.8Why explain in military simulation2.9Risks of opaque agents2.10Laboratory: a reinforcement learning agent in a simulation environment
3.1Explaining reinforcement learning policies3.2Distilled decision trees3.3Attention and explanation of sequences3.4Causal explanations3.5Visualising learned strategies3.6Evaluating the quality of explanations3.7Misleading explanations and fidelity3.8Attacks on explanation methods3.9Instructor cognitive load3.10Practice: SHAP explanation of a simulation agent
4.1Calibrated trust in AI systems4.2Automation bias and distrust4.3XAI-supported after action review4.4Student learning from AI4.5Transfer of simulated strategies to the real world4.6Assessing students using AI4.7Fairness in assessment4.8Transparency towards students4.9NATO principles: explainability and traceability4.10Case study: an explainable debrief of an exercise
5.1Explainability as a design requirement5.2Documentation of models and scenarios5.3Auditing simulation systems5.4Accountability for decisions based on simulation5.5Use of simulation in Article 36 reviews5.6Academic research in defence XAI5.7Publication and dual use5.8Procurement requirements5.9Explainability indicators5.10Workshop: explainability requirements for a simulator
6.1Definition of the simulation scenario6.2Development of the AI agent6.3Selection of explanation methods6.4Evaluation of explanation fidelity6.5User testing6.6Ethical and trust analysis6.7Documentation and traceability6.8Usage recommendations6.9Report and presentation6.10Final review with the tutor
How you'll learn
Fully 100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, making it easy to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is SHAP, LIME, Python (PyTorch), Unity ML-Agents, in free, academic or evaluation versions. Tests are studied using real laboratory procedures for model explainability, simulation of decision-making agents and user trust assessments. Assessment is continuous, module by module, plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Explain the concepts and techniques of explainability in AI.
Analyse the use of intelligent agents in military simulation.
Apply explanation techniques to decision-making agents.
Evaluate the calibration of user trust in AI.
Identify transparency and human oversight requirements.
Where this takes you
Requirements
- No prior degree is required.
- Internet connection and a computer capable of running the programme's software.
- Spanish language level sufficient to follow technical regulatory texts.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours, spread over 3 to 5 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.
You work with SHAP, LIME, Python (PyTorch), Unity ML-Agents. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
An SEIUM own diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the higher programme. Please check the recognition policy when you enrol.
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