Diploma in Legal Auditing of AI in Defence
Online postgraduate diploma of 800 hours in legal auditing of AI in defence, structured in 8 modules covering AI uses and risks in defence, the applicable legal framework, AI audit methodologies, data and model auditing, human oversight and accountability, procurement and suppliers, and audit reporting, with an assigned technical tutor.
Diploma in Legal Auditing of AI in Defence — studying from the United Kingdom
The United Kingdom maintains a substantial defence industry, with prime contractors such as BAE Systems and Babcock, and a wide supply chain across the Midlands, the North West, Bristol and Scotland. Land systems, armoured vehicles, munitions and military engineering programmes provide long-term employment for engineers in design, integration, test and sustainment. The Ministry of Defence, Defence Equipment and Support and the Defence Science and Technology Laboratory oversee procurement and research. Security clearance requirements shape recruitment, and professional standards are maintained through UK defence engineering frameworks.
Fees for the United Kingdom: £1,250 (Pound sterling), with instalments and employer sponsorship available.
Relevant bodies in the United Kingdom
Typical roles
Questions from the United Kingdom
Which UK bodies and regulators are relevant to defence and military land systems engineering?
In the UK, the Ministry of Defence sets its own engineering standards and the Engineering Council regulates professional registration. Professional bodies such as the Institution of Mechanical Engineers (IMechE) and the Royal Engineers' professional structures are relevant. SEIUM's qualifications are private and not accredited by these bodies, so recognition for security-cleared or MOD roles is decided by the employer and the relevant authority.
Will a private qualification help with UK defence industry careers?
UK defence employers, including primes and suppliers, often prioritise security clearance eligibility, relevant experience and formal qualifications recognised by the MOD or industry bodies. A private qualification may support your profile but is unlikely to replace these requirements. Ask prospective employers how they would assess it before enrolling.
Is it practical to study this online while working in the UK, and what about language and funding?
Online study means you can continue working in the UK, and no student visa is needed to study from home. Teaching is in English, so good technical English is essential. Fees can be paid in instalments, and some employers offer training sponsorship, though policies vary. Each programme has a fixed number of hours and an assigned technical tutor. Confirm the workload and costs before enrolling.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Identify the uses and legal risks of AI in defence.
Apply the international, European and national legal framework.
Design audit programmes for AI systems.
Audit machine learning data and models.
Assess human oversight and accountability.
Review AI contracts and suppliers.
Write audit reports with recommendations.
Who it's for
- AI systems auditors.
- Defence legal advisers.
- Regulatory compliance managers.
- AI governance consultants.
- Technology risk analysts.
- Data protection officers working with defence organisations.
- Engineering or science graduates seeking to enter the defence sector.
What you'll work with
- Regulation (EU) 2024/1689 (AI Act) (EU harmonised rules on artificial intelligence)
- Additional Protocol I to the Geneva Conventions (art. 36) (legal review of new weapons)
- ISO/IEC 42001:2023 (AI management systems)
- ISO 19011:2018 (guidelines for auditing management systems)
- Organic Law 7/2021 (Spanish law on personal data processed for law enforcement and security purposes)
- Law 24/2011 (Spanish public sector contracts in defence and security)
- Regulation (EU) 2021/821 (EU dual-use export control regime)
- ISO/IEC 23894:2023 (AI risk management)
- IBM AI Fairness 360
- Microsoft Responsible AI Toolbox
- MLflow
- Python (SHAP)
8 modules
1.1Uses in logistics and maintenance1.2Uses in intelligence and analysis1.3Uses in command and control1.4Autonomy in platforms1.5Associated legal risks1.6Risk-based classification of uses1.7The Ministry of Defence AI strategy1.8NATO principles of responsible AI1.9Audit roles1.10Case study: inventory of AI systems
2.1International humanitarian law2.2Article 36 legal review2.3Human rights2.4The AI Act and the defence exclusion2.5Organic Law 7/20212.6Public procurement in defence2.7The dual-use regulation2.8Financial and criminal liability2.9Information security regulations2.10Workshop: regulatory map of an AI system
3.1Types of AI audit3.2Scope and criteria3.3Audit evidence3.4Auditing ISO/IEC 42001 management systems3.5ISO 19011 guidelines3.6Public frameworks for algorithmic auditing3.7IEEE standards on AI3.8Audit planning3.9Auditor independence3.10Practical exercise: audit programme
4.1Training data4.2Bias and representativeness4.3Data quality4.4Model documentation4.5Robustness4.6Explainability4.7Performance testing4.8Traceability4.9Automatic logging4.10Lab: bias audit with AI Fairness 360
5.1Meaningful human control5.2Chain of command5.3Decision records5.4Allocation of responsibilities5.5Operator training5.6Interface design5.7Operating procedures5.8Incident management5.9Accountability5.10Case study: audit of human oversight
6.1AI contract clauses6.2Rights over data and models6.3Transparency obligations6.4Due diligence6.5AI supply chain6.6Export controls6.7Supplier auditing6.8Intellectual property6.9Confidentiality6.10Workshop: audit clauses in a contract
7.1Classification of findings7.2Severity and prioritisation7.3Recommendations7.4Writing the report7.5Action follow-up7.6Communicating results7.7Handling classified information7.8Continuous improvement7.9Compliance indicators7.10Practical exercise: writing an audit report
8.1System selection8.2Applicable regulatory framework8.3Audit plan8.4Data and model audit8.5Human oversight audit8.6Findings8.7Recommendations8.8Conclusions8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
The programme is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so it can be combined with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is IBM AI Fairness 360, Microsoft Responsible AI Toolbox, MLflow and Python (SHAP), in free, academic or evaluation versions. Exercises are based on real procedures for bias audits of models, human oversight reviews and contractual analysis of AI systems. Assessment is continuous by module, plus the final project.
Standards covered: Regulation (EU) 2024/1689 (AI Act), Additional Protocol I to the Geneva Conventions (art. 36), ISO/IEC 42001:2023, ISO 19011:2018, Organic Law 7/2021, Law 24/2011, Regulation (EU) 2021/821, ISO/IEC 23894:2023.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
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 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with IBM AI Fairness 360, Microsoft Responsible AI Toolbox, MLflow and Python (SHAP), using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the software, and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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