Overview of the course
Module 1: Foundations of AI Governance
By the end of this module, you will:
Have a comprehensive understanding of the AI in education landscape
Be able to identify the risk categories as outlined in the EU AI Act
Recognise the different types of AI systems commonly used in schools
Understand the key components of the AI lifecycle in educational settings
You will be able to:
Lead an audit of AI tools in your setting using our provided AI Inventory Template
Classify existing AI systems according to EU AI Act risk categories
Document AI system purposes and intended educational outcomes
EU AI Act alignment:
Article 3 definitions and classification framework
Risk-based approach to AI governance (Articles 5-7)
Documentation requirements for high-risk systems (Annex IV)
Practical tools:
AI Inventory Assessment Template
AI Risk Classification Worksheet
Staff Training Slide Deck Template
Quick Reference Guide to AI in Education
End of week 1: "I can audit the AI systems in my school using a structured approach similar to a DPIA."
Module 2: AI Governance Frameworks and Ethical Considerations
By the end of this module, you will:
Understand the structure of an effective AI governance framework for educational institutions
Know how to integrate AI principles into existing school policies
Be able to identify ethical issues specific to AI use with children and young people
Recognise bias risks in AI educational tools and mitigation strategies
You will be able to:
Draft an AI governance policy for your educational setting
Define clear roles and responsibilities for AI oversight
Create an ethical framework for AI use specific to your institution
Set up a governance committee structure with appropriate stakeholder representation
EU AI Act alignment:
Governance requirements for providers and users (Articles 16-29)
Quality management systems (Article 17)
Risk management obligations (Article 9)
Requirements for human oversight (Article 14)
Practical tools:
AI Governance Policy Template
AI Ethics Framework Builder
Stakeholder Mapping Tool
Roles and Responsibilities Matrix
End of week 2: "I can establish an AI governance structure in my school that defines clear lines of accountability and responsibility."
Module 3: Data Protection and Regulations for Vulnerable Groups
By the end of this module, you will:
Understand the specific requirements for processing children's data under GDPR and the EU AI Act
Know how to implement enhanced protections for vulnerable learners
Be able to navigate multi-jurisdictional compliance requirements
Recognise the unique privacy concerns in educational AI applications
You will be able to:
Conduct a child-specific Data Protection Impact Assessment (DPIA)
Implement appropriate technical and organisational measures for data protection
Create lawful basis documentation for AI systems processing student data
Develop age-appropriate privacy notices and consent mechanisms
EU AI Act alignment:
Data governance requirements (Article 10)
Transparency obligations (Article 13)
Processing of special categories of data (alignment with GDPR Article 9)
Record-keeping obligations (Article 18)
Practical tools:
Child-Specific DPIA Template
Regulatory Compliance Checklist
Data Processing Inventory Worksheet
Age-Appropriate Privacy Notice Templates
End of week 3: "I can assess an AI system's compliance with child data protection requirements and implement appropriate safeguards."
Module 4: Risk Assessment and Mitigation for Educational AI
By the end of this module, you will:
Understand the methodology for AI risk assessment in educational contexts
Know how to identify and categorise AI-specific risks to learners
Be able to develop targeted mitigation strategies for identified risks
Recognise when to escalate high-risk AI applications for external assessment
You will be able to:
Conduct a comprehensive AI risk assessment using structured methodologies
Create a risk register specific to AI applications in your setting
Develop and implement mitigation strategies for identified risks
Establish incident response protocols for AI-related issues
EU AI Act alignment:
Risk management system requirements (Article 9)
Technical documentation (Annex IV)
Conformity assessment procedures (Articles 43-44)
Post-market monitoring (Article 61)
Practical tools:
AI Risk Assessment Matrix
Risk Mitigation Planning Template
AI Incident Response Playbook
Risk Register for Educational AI Systems
End of week 4: "I can systematically identify, assess, and mitigate risks associated with AI systems used in my school."
Module 5: AI System Evaluation and Selection
By the end of this module, you will:
Understand how to evaluate AI products for educational use
Know what technical documentation to request from vendors
Be able to conduct due diligence on AI providers
Recognise red flags in AI product claims and marketing
You will be able to:
Create procurement guidelines for AI systems
Develop evaluation criteria aligned with the EU AI Act
Conduct effective vendor assessments
Draft contractual requirements for AI providers
EU AI Act alignment:
Technical documentation requirements (Article 11)
Conformity assessment procedures (Articles 43-44)
Provider obligations (Articles 16-24)
Transparency requirements (Article 13)
Practical tools:
AI Procurement Guidelines
Vendor Assessment Questionnaire
AI Product Evaluation Rubric
Contract Requirements Checklist
End of week 5: "I can lead a structured evaluation process for selecting appropriate and compliant AI systems for my school."
Module 6: Transparency and Communication Strategies
By the end of this module, you will:
Understand the transparency requirements under the EU AI Act
Know how to effectively communicate about AI use to different stakeholders
Be able to create clear documentation about AI systems for various audiences
Recognise effective strategies for building trust around AI use
You will be able to:
Develop transparency notices for different AI applications
Create communication plans for staff, students, and parents
Design informational materials explaining AI use in your setting
Facilitate stakeholder dialogues about AI implementation
EU AI Act alignment:
Transparency obligations (Article 13)
Information provision requirements (Article 52)
High-risk system user instructions (Article 13)
Registration requirements (Article 51)
Practical tools:
AI Transparency Notice Templates
Stakeholder Communication Plan
AI Information Sheet Templates
Parent/Guardian Meeting Toolkit
End of week 6: "I can create transparent communications about AI use that build trust among students, parents, and staff."
Module 7: Monitoring, Auditing, and Continuous Improvement
By the end of this module, you will:
Understand post-implementation monitoring requirements for AI systems
Know how to establish audit procedures for AI applications
Be able to create continuous improvement mechanisms
Recognise performance metrics for ethical AI deployment
You will be able to:
Implement ongoing monitoring protocols for AI systems
Conduct internal audits of AI applications
Establish review cycles and improvement processes
Create performance dashboards for AI governance
EU AI Act alignment:
Post-market monitoring requirements (Article 61)
Quality management system requirements (Article 17)
Notification of serious incidents (Article 62)
Market surveillance provisions (Articles 63-68)
Practical tools:
AI Monitoring Plan Template
AI Audit Checklist
Continuous Improvement Framework
AI Performance Metrics Dashboard
End of week 7: "I can implement structured monitoring and audit processes to ensure ongoing compliance and improvement of AI systems."
Module 8: Incident Response and Crisis Management
By the end of this module, you will:
Understand AI-specific incident types and response requirements
Know how to identify, classify, and respond to AI-related incidents
Be able to create effective crisis management plans
Recognise notification and reporting obligations
You will be able to:
Develop an AI incident response plan
Create incident classification criteria
Establish notification procedures for serious incidents
Design post-incident review processes
EU AI Act alignment:
Incident notification requirements (Article 62)
Market surveillance provisions (Articles 63-68)
Corrective action requirements (Article 65)
Documentation and reporting obligations
Practical tools:
AI Incident Response Plan Template
Incident Classification Matrix
Notification Process Flowchart
Post-Incident Review Framework
End of week 8: "I can lead effective responses to AI-related incidents and fulfill all notification and reporting obligations."
Module 9: Training and Capacity Building
By the end of this module, you will:
Understand the training needs for different stakeholder groups
Know how to build AI literacy among staff and students
Be able to design effective training programmes
Recognise strategies for developing ongoing capacity
You will be able to:
Conduct training needs assessments for AI governance
Develop role-specific training materials
Create an AI literacy curriculum for students
Establish a continuous learning framework for staff
EU AI Act alignment:
Human oversight requirements (Article 14)
Competence requirements for staff (implied in various provisions)
User obligations regarding training and monitoring (Article 29)
Technical knowledge requirements for conformity assessment
Practical tools:
AI Training Needs Assessment
Role-Specific Training Templates
Student AI Literacy Curriculum
Continuous Learning Framework
End of week 9: "I can implement comprehensive AI training programmes for all stakeholders in my educational setting."
Module 10: Capstone Project and Certification
By the end of this module, you will:
Synthesise all components into a comprehensive AI governance plan
Know how to implement a phased approach to AI governance
Be able to demonstrate mastery of key AI governance concepts
Successfully complete your certification requirements
You will be able to:
Create a complete AI governance implementation plan for your institution
Present and defend your governance strategy
Integrate all compliance elements into a cohesive framework
Meet all certification requirements for the AI Governance Officer credential
EU AI Act alignment:
Comprehensive integration of all relevant provisions
Demonstration of compliance with the risk-based approach
Implementation of required governance structures
Documentation of all necessary compliance elements
Practical tools:
AI Governance Implementation Plan Template
Certification Examination Preparation Guide
Presentation Template for Defense
Complete AI Governance Documentation Set
End of week 10: "I can implement a comprehensive AI governance programme in my educational setting that ensures compliance, promotes ethical use, and supports positive educational outcomes."
Additional Program Features:
Weekly recorded content: Learning content delivered through video with accompanying written materials and quick assessments.
Weekly Live Sessions: Interactive webinars to build on learning content for the week.
Peer Learning Communities: Small groups for collaboration and support
Office Hours: Weekly opportunities for personalised guidance
Resource Library: Comprehensive collection of templates, checklists, and examples
Post-Certification Support: Monthly updates on regulatory changes and emerging practices
Networking Directory: Connect with other certified professionals in
Assessment Strategy:
Weekly Application Exercises: Demonstrating practical application of concepts
Mid-Program Review: Feedback on governance framework development
Capstone Project: Complete AI governance plan for educational setting
Final Assessment: Comprehensive examination covering all programme areas
Practical Implementation Evidence: Documentation of actual implementation steps