Artificial Intelligence And Block Chain

Training Course on Artificial Intelligence (AI) Regulations-EU AI Act

Introduction

Artificial Intelligence (AI) is revolutionizing industries worldwide, but its growth demands responsible governance and legal oversight. The EU Artificial Intelligence Act (EU AI Act) stands as the first comprehensive regulatory framework designed to manage AI risks and ensure safe deployment within the European Union. Training Course on Artificial Intelligence (AI) Regulations – EU AI Act provides a future-ready, compliance-driven, and ethically aligned curriculum to help professionals, regulators, and developers adapt to evolving standards. It emphasizes risk-based classification, AI transparency, data governance, and user protection.

In an era marked by AI-powered innovations, understanding legal, ethical, and compliance dimensions is critical for sustainable growth. With GDPR synergy, automated decision-making standards, and AI accountability, this course offers practical insights into implementing compliant AI systems. Participants will gain real-world knowledge through case studies, regulatory breakdowns, and strategic risk assessments. Whether you are a policymaker, engineer, or executive, this course ensures you stay compliant, competitive, and responsible.

Programme Curriculum

Training Course on Artificial Intelligence (AI) Regulations-EU AI Act

Introduction

Course Objectives

Understand the core principles and structure of the EU AI Act.
Identify AI risk categories: unacceptable, high-risk, limited-risk, and minimal-risk systems.
Evaluate data governance and algorithmic accountability in high-risk AI systems.
Examine transparency and explainability mandates for AI developers.
Understand GDPR implications and interoperability with the EU AI Act.
Learn documentation, record-keeping, and conformity assessment obligations.
Implement human oversight mechanisms in AI operations.
Assess the role of post-market monitoring and risk management.
Compare global AI regulations and the EU’s strategic leadership.
Apply ethical AI frameworks in regulatory compliance.
Learn the enforcement roles of national competent authorities.
Navigate AI innovation within regulatory sandboxes.
Conduct compliance audits and technical documentation reviews

Target Audience

Legal professionals in tech law
Compliance officers in AI-driven industries
Government policymakers and regulators
AI and ML developers
Data protection officers (DPOs)
Tech company executives
Academic researchers in AI ethics
Start-up founders in the AI domain

Course Duration: 10 days

Course Modules

Module 1: Introduction to AI Governance

Evolution of AI regulation in Europe
Scope and objectives of the EU AI Act
Defining AI under the EU framework
Risk-based classification of AI systems
Stakeholder responsibilities
Case Study: Facial recognition bans in public surveillance

Module 2: Understanding Risk Categories in AI

Unacceptable risk AI systems
High-risk system identification
Requirements for limited and minimal risk
Use-case scenarios
Penalties and consequences
Case Study: Real-time biometric surveillance in transportation

Module 3: Data Governance and AI

Data quality and dataset governance
Bias prevention and diversity
Secure data acquisition practices
Recordkeeping under Article 10
Human review of data handling
Case Study: AI in credit scoring systems

Module 4: Transparency and User Rights

Obligations for transparency
Notification of AI interaction
User awareness strategies
Automated decision-making rules
Non-discrimination safeguards
Case Study: Chatbot disclosures in public services

Module 5: Human Oversight in AI Systems

Role of human-in-the-loop mechanisms
Prevention of automation bias
Manual override procedures
Risk mitigation techniques
Operator responsibilities
Case Study: AI in healthcare diagnostics

Module 6: Conformity Assessment Procedures

CE marking for AI systems
Third-party audit mechanisms
Technical documentation essentials
Compliance verification steps
Harmonized standards application
Case Study: CE compliance in robotic process automation

Module 7: Post-Market Monitoring & Risk Management

Continuous risk assessment
Monitoring system performance
Incident reporting under Article 65
Corrective actions
Cybersecurity alignment
Case Study: AI malfunction in autonomous vehicles

Module 8: GDPR and the EU AI Act

Comparing GDPR and AI Act
Personal data processing in AI
Consent under AI operations
Data minimization principles
Rights of data subjects
Case Study: AI hiring tools and data privacy

Module 9: Enforcement Mechanisms

Role of national supervisory authorities
Penalties for non-compliance
Investigation powers
Prohibition orders
Redress mechanisms
Case Study: Enforcement action against an AI startup

Module 10: Regulatory Sandboxes

Innovation-friendly environments
Risk-controlled testing
Sandbox eligibility and criteria
Benefits for SMEs
Collaboration with authorities
Case Study: Testing AI-based mental health apps

Module 11: Global Comparisons in AI Regulation

U.S. AI policy overview
China’s AI ethical framework
OECD AI principles
Regulatory fragmentation
Cross-border compliance strategies
Case Study: Cross-border AI medical diagnostics

Module 12: Ethical Considerations in AI

Fairness, accountability, and transparency
Bias reduction strategies
Societal impact analysis
Inclusive design practices
Long-term risk forecasting
Case Study: Ethical AI deployment in public housing

Module 13: Industry-Specific Implications

AI in finance and insurance
AI in transportation and logistics
Healthcare and medical AI
Educational technology and AI
AI in defense and security
Case Study: Predictive policing tools and risk

Module 14: Technical Documentation and Audit Preparation

Preparing technical files
Compliance audit strategies
Required documentation elements
Version control and system logs
Responding to regulator inquiries
Case Study: Audit readiness in a health AI company

Module 15: Future Trends in AI Regulation

Evolution of EU AI policy post-2025
Quantum AI and regulation gaps
AI and green policy alignment
Anticipating ethical dilemmas
Role of civil society in oversight
Case Study: AI and environmental decision systems

Training Methodology

Instructor-led virtual or in-person training sessions
Interactive case study workshops
AI compliance simulation exercises
Downloadable toolkits and checklists
Quizzes and knowledge assessments
Final capstone project and certification

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

AI Governance Legal Compliance Ethics Technology Regulation

Programme Fee

Duration: 10 Days

Method: Online or Physical

Online Price: $2,000

Physical Price: $3,000

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $2,000