Introduction

In today’s digital economy, artificial intelligence (AI) is transforming industries through automation, predictive analytics, and personalized experiences. However, as AI systems handle vast amounts of personal and sensitive data, they introduce significant privacy and data protection concerns. Training Course on The Intersection of AI and Data Protection explores the regulatory, technical, and ethical considerations organizations must address to ensure compliance and maintain trust in AI systems.

This training empowers participants to navigate global data protection laws like GDPR, CCPA, and emerging AI regulations while deploying AI responsibly. Through in-depth modules, real-world case studies, and interactive learning, participants will gain practical tools to mitigate AI risks, ensure lawful data processing, and align innovation with compliance.

Programme Curriculum

Training Course on The Intersection of AI and Data Protection

Introduction

Course Objectives

Understand AI governance and its relationship with data privacy laws.
Explore GDPR compliance in AI-driven data processing.
Identify and mitigate AI data security risks.
Evaluate automated decision-making under global data protection frameworks.
Apply privacy-by-design in AI system development.
Assess the impact of machine learning on individual privacy rights.
Interpret the role of data anonymization and differential privacy in AI.
Examine AI transparency and explainability techniques.
Navigate legal challenges of AI ethics and accountability.
Analyze real-time AI data breaches and incident response.
Comply with cross-border data transfer laws in AI contexts.
Develop robust AI risk assessment frameworks.
Master AI audit trails and documentation for regulatory compliance.

Target Audience

Data Protection Officers (DPOs)
Compliance Officers
AI Developers and Engineers
IT Security Professionals
Privacy Consultants
Corporate Legal Counsel
Risk Management Professionals
Policy Makers and Regulators

Course Duration: 5 days

Course Modules

Module 1: Introduction to AI and Data Protection

Overview of AI and machine learning models
Key concepts of personal data and data processing
History and evolution of data protection laws
The convergence of AI and privacy concerns
Global regulatory frameworks (GDPR, CCPA, etc.)
Case Study: Google DeepMind & NHS data-sharing controversy

Module 2: Legal & Ethical Frameworks

Understanding GDPR articles relevant to AI
Consent, legitimate interest, and transparency
Automated decision-making and profiling
Ethical implications of AI bias
Compliance checklists and frameworks
Case Study: Facial recognition and EU legal challenges

Module 3: Privacy by Design and Default in AI

Embedding privacy in AI architecture
Differential privacy and federated learning
Data minimization and purpose limitation
Privacy impact assessments (PIAs)
Best practices for ethical AI development
Case Study: Apple’s implementation of differential privacy

Module 4: AI Risk Management and Governance

Identifying AI risks and vulnerabilities
AI governance models and frameworks
Risk mitigation strategies for AI systems
Establishing accountability in AI projects
Aligning business objectives with compliance
Case Study: IBM Watson and risk mismanagement in healthcare

Module 5: Data Anonymization & Security in AI

Techniques for anonymizing datasets
Re-identification risks in AI analytics
Secure data lifecycle management
Encryption and data masking strategies
Regulatory standards for AI data security
Case Study: Netflix dataset re-identification incident

Module 6: AI Transparency and Explainability

Importance of explainable AI (XAI)
Building user trust through transparency
Tools and methods for explainability
Regulatory push for AI accountability
Documenting AI decision-making processes
Case Study: COMPAS algorithm in U.S. criminal justice

Module 7: Cross-Border Data Transfers and AI

Overview of data transfer mechanisms (SCCs, BCRs)
AI compliance in multinational operations
Impact of Schrems II and data localization laws
Role of cloud providers in data movement
Risk assessment for international data flows
Case Study: Meta’s data transfer suspension in Europe

Module 8: Building a Responsible AI Strategy

Framework for ethical AI adoption
Auditing AI systems for bias and compliance
Stakeholder engagement and training
Continuous monitoring and policy updates
Integrating data protection into AI lifecycle
Case Study: Microsoft’s Responsible AI initiative

Training Methodology

Instructor-led virtual sessions with live Q&A
Interactive workshops using real-world scenarios
Hands-on case study analysis for experiential learning
Quizzes and assessments for knowledge reinforcement
Downloadable toolkits and compliance templates
Peer collaboration forums for shared learning

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 Data Privacy Compliance Technology

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000