A tailored course, built for your situation
Mastering AI Act for Computer Programmers in High-Velocity Compliance Environments
Turn regulatory intent into working code faster with a structured path through AI governance requirements.
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Spending too long interpreting regulations before writing code?
The situation this course is for
Regulatory texts can be dense and open-ended, creating delays between policy alignment and implementation. For engineers in fast-moving environments, this lag breaks flow and adds rework.
Who this is for
Computer Programmer working in a regulated tech environment, responsible for implementing AI systems that must comply with emerging legislation.
Who this is not for
This is not for compliance officers who don’t write code or engineers working outside AI-adjacent systems.
What you walk away with
- Translate AI Act articles directly into technical controls and implementation tasks
- Produce compliance-ready documentation as a byproduct of development
- Reduce time from regulation publication to artefact deployment by up to 50%
- Anticipate auditor questions and embed answers in code comments and design docs
- Confidently ship AI features with built-in compliance scaffolding
The 12 modules (with all 144 chapters)
Module 1. Understanding the AI Act Scope
Break down which provisions apply to which types of AI systems, with a focus on classification relevant to developer workflows.
12 chapters in this module
- Scope of AI Act
- High-Risk Category Definition
- AI System Classification
- Developer Responsibilities
- Regulatory Jurisdiction
- Timeline for Enforcement
- Exemptions and Exclusions
- Interaction with Other Laws
- Sector-Specific Rules
- Obligations by Role
- Third-Party Dependencies
- Internal Documentation Needs
Module 2. Mapping Obligations to Code
Turn legal requirements into testable, implementable code standards with traceable logic.
12 chapters in this module
- Article to Artefact Framework
- Data Provenance Controls
- Model Transparency Rules
- Accuracy Benchmarks
- Human Oversight Design
- Logging Requirements
- Input Validation Standards
- Output Monitoring Logic
- Error Handling Protocols
- Version Control Alignment
- Audit Trail Generation
- Compliance-Driven Testing
Module 3. Building Compliance into CI/CD
Embed AI Act checks directly into development pipelines to catch issues early and automatically.
12 chapters in this module
- Pipeline Integration Points
- Pre-Commit Hooks
- Automated Policy Checks
- Static Code Analysis
- Dynamic Testing Triggers
- Fail-Safe Thresholds
- Artifact Tagging System
- Compliance Gate Design
- Rollback Conditions
- Team Notification Rules
- Integration with Jira
- CI/CD Audit Logging
Module 4. Documentation as Code
Generate required compliance documentation automatically from codebases and version history.
12 chapters in this module
- Docs from Comments
- Schema Definition Files
- Auto-Generated User Manuals
- Technical Documentation Templates
- Version Diff Summaries
- Change Justification Logs
- Regulatory Mapping Matrix
- Compliance Evidence Export
- Standard Output Formats
- Reviewer Access Design
- Redaction Rules
- Retention Policies
Module 5. Working with Notified Bodies
Prepare for external assessments by generating evidence packages that match auditor expectations.
12 chapters in this module
- Notified Body Role
- Assessment Preparation
- Evidence Packaging
- Gap Self-Assessment
- Internal Audit Process
- Findings Response Protocol
- Corrective Action Tracking
- Certification Timeline
- Surveillance Audit Prep
- External Communication Rules
- Escalation Path Setup
- Post-Certification Monitoring
Module 6. Managing Third-Party Models
Apply AI Act rules to off-the-shelf or open-source models integrated into your stack.
12 chapters in this module
- Model Origin Tracking
- Risk Classification
- Vendor Due Diligence
- License Compatibility
- Model Card Review
- Performance Baseline
- Fine-Tuning Impact
- Embedding Compliance
- Dependency Mapping
- Security Patching
- Usage Restrictions
- Compliance Warranty
Module 7. Human Oversight Design
Implement meaningful human review points that satisfy AI Act requirements and improve system quality.
12 chapters in this module
- Oversight Points
- Alert Thresholds
- Review Interface Design
- Decision Logging
- Override Mechanism
- Escalation Rules
- Reviewer Qualifications
- Training Requirements
- Audit Trail Integrity
- Response Time SLA
- False Positive Handling
- Periodic Review Cycle
Module 8. Bias and Fairness Testing
Operationalize fairness assessments to meet AI Act non-discrimination requirements.
12 chapters in this module
- Bias Detection Methods
- Data Drift Monitoring
- Representative Sampling
- Disparate Impact Analysis
- Model Audit Tools
- Fairness Metrics
- Threshold Calibration
- Root Cause Investigation
- Remediation Actions
- Documentation Needs
- Stakeholder Review
- Public Reporting
Module 9. Security and Robustness
Meet AI Act requirements for resilience and protection against attacks.
12 chapters in this module
- Adversarial Attack Types
- Model Hardening
- Input Sanitization
- System Monitoring
- Threat Modeling
- Resilience Testing
- Fail-Safe Design
- Penetration Testing
- Access Controls
- Encryption Needs
- Incident Response
- Security Patch Management
Module 10. Data Governance Alignment
Ensure training and operational data practices comply with both GDPR and AI Act.
12 chapters in this module
- Lawful Basis
- Consent Tracking
- Data Minimization
- Purpose Limitation
- Anonymization Standards
- Data Quality Checks
- Source Verification
- Storage Limits
- Cross-Border Rules
- Subject Rights Support
- Data Subject Access
- Data Portability
Module 11. Incident Response and Reporting
Build systems that detect, log, and report AI incidents in line with regulatory timelines.
12 chapters in this module
- Incident Definition
- Detection Mechanisms
- Escalation Path
- Internal Logging
- External Notification
- Timeframe Compliance
- Regulator Contact
- Public Communication
- Root Cause Analysis
- Remediation Plan
- System Updates
- Follow-Up Reporting
Module 12. Scaling Compliance Across Teams
Propagate AI Act implementation patterns across engineering groups without central bottlenecks.
12 chapters in this module
- Pattern Library
- Internal Advocates
- Training Rollout
- Cross-Team Sync
- Standard Templates
- Compliance Champion
- Tooling Access
- Feedback Loop
- Knowledge Sharing
- Version Control
- Policy Updates
- Scaling Metrics
How this maps to your situation
- Regulatory interpretation phase
- Development sprint with compliance needs
- Audit preparation cycle
- Cross-team rollout of standards
Before vs. after
Before
Regulatory texts require slow, manual translation into technical tasks, creating delays and rework.
After
Move directly from AI Act article to implementation with structured templates and built-in documentation.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3 hours per module, designed to be consumed alongside active development work.
If nothing changes
Without a clear method, engineers risk delays, audit findings, or rework due to misaligned implementation.
How this compares to the alternatives
Unlike generic compliance courses, this program is built specifically for programmers implementing AI systems, with direct mappings from law to code.
Frequently asked
Is this course for developers or compliance officers?
It is specifically designed for developers who must implement AI systems that comply with the AI Act.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Do I need legal training to take this course?
No. It translates legal requirements into technical actions without assuming prior legal knowledge.
$199 one-time. Approximately 3 hours per module, designed to be consumed alongside active development work..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours