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Duration 14 hours
Course Outline
Foundations: The EU AI Act for Technical Teams
- Key obligations and terminology relevant to developers and operators
- A technical analysis of prohibited practices under Article 4
- Translating legal requirements into actionable engineering controls
Secure and Compliant Development Lifecycle
- Establishing repository structures and implementing policy-as-code for AI projects
- Conducting code reviews and automated static checks for risky patterns
- Managing dependencies and supply chains for model components
CI/CD Pipeline Design for Compliance
- Defining pipeline stages: build, test, validation, packaging, and deployment
- Integrating governance gates and automated policy checks into the workflow
- Ensuring artifact immutability and tracking provenance
Model Testing, Validation, and Safety Checks
- Performing data validation and bias detection tests
- Assessing performance, robustness, and resilience against adversarial attacks
- Defining automated acceptance criteria and generating test reports
Model Registry, Versioning, and Provenance
- Utilising MLflow or similar tools for model lineage and metadata management
- Versioning models and datasets to ensure reproducibility
- Documenting provenance and creating audit-ready artifacts
Runtime Controls, Monitoring, and Observability
- Instrumenting systems to log inputs, outputs, and decision-making processes
- Monitoring for model drift, data drift, and key performance metrics
- Implementing alerting, automated rollback, and canary deployment strategies
Security, Access Control, and Data Protection
- Applying least-privilege IAM policies to model training and serving environments
- Safeguarding training and inference data both at rest and in transit
- Implementing robust secrets management and secure configuration practices
Auditability and Evidence Collection
- Producing machine-readable logs alongside human-readable summaries
- Aggregating evidence for conformity assessments and external audits
- Enforcing retention policies and secure storage for compliance artifacts
Incident Response, Reporting, and Remediation
- Identifying suspected prohibited practices or safety incidents
- Executing technical steps for containment, rollback, and mitigation
- Drafting technical reports for governance bodies and regulatory authorities
Summary and Next Steps
Requirements
- Proficiency in software development and deployment workflows
- Practical experience with containerisation and fundamental Kubernetes concepts
- Working knowledge of Git-based source control and CI/CD methodologies
Target Audience
- Developers creating or maintaining AI-based components
- DevOps and platform engineers overseeing deployment processes
- System administrators managing infrastructure and runtime environments
