Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Foundations: EU AI Act for Technical Teams
- Key obligations and terminology relevant to developers and operators
- Technical perspective on prohibited practices under Article 4
- Translating legal requirements into specific engineering controls
Secure and Compliant Development Lifecycle
- Repository structure and policy-as-code implementation for AI projects
- Code review and automated static analysis for identifying risky patterns
- Dependency and supply-chain management for model components
CI/CD Pipeline Design for Compliance
- Pipeline stages: build, test, validation, package, and deploy
- Integration of governance gates and automated policy checks
- Ensuring artifact immutability and provenance tracking
Model Testing, Validation, and Safety Checks
- Data validation and bias detection testing protocols
- Assessing performance, robustness, and adversarial resilience
- Defining automated acceptance criteria and generating test reports
Model Registry, Versioning, and Provenance
- Utilizing MLflow or equivalent tools for model lineage and metadata management
- Versioning models and datasets to ensure reproducibility
- Recording provenance data and creating audit-ready artifacts
Runtime Controls, Monitoring, and Observability
- Instrumentation for logging inputs, outputs, and decision-making processes
- Monitoring model drift, data drift, and key performance metrics
- Implementing alerting, automated rollback, and canary deployments
Security, Access Control, and Data Protection
- Applying least-privilege IAM strategies for training and serving environments
- Safeguarding training and inference data both at rest and in transit
- Best practices for secrets management and secure configuration
Auditability and Evidence Collection
- Generating machine-readable logs alongside human-readable summaries
- Packaging evidence for conformity assessments and regulatory audits
- Defining retention policies and secure storage for compliance artifacts
Incident Response, Reporting, and Remediation
- Identifying suspected prohibited practices or safety incidents
- Technical procedures for containment, rollback, and mitigation
- Drafting technical reports for governance bodies and regulators
Summary and Next Steps
Requirements
- A solid grasp of software development and deployment workflows
- Experience with containerization and fundamental Kubernetes concepts
- Familiarity with Git-based source control and CI/CD practices
Target Audience
- Developers responsible for building or maintaining AI components
- DevOps and platform engineers overseeing deployment processes
- Administrators managing infrastructure and runtime environments
