AED
UAD Dirham
Code: AED
Mentor Based
GDPR & AI Data Privacy for Teams
Empower Your Team—Build AI Responsibly with Data Privacy by Design.
Early access to the e-LMS platform is included
About This Course
“GDPR & AI Data Privacy for Teams” is a targeted training program designed for cross-functional teams working with or deploying AI technologies. The course demystifies GDPR in the AI context—explaining how to collect, process, and store data responsibly, conduct risk assessments, manage consent, and design AI systems that comply with data protection laws. Whether you are in product, engineering, legal, marketing, or data science, this course offers a unified foundation for responsible AI deployment in line with European privacy standards.
Aim
To equip professionals and teams with essential knowledge of the General Data Protection Regulation (GDPR) and its application in Artificial Intelligence (AI) systems, ensuring compliance, ethical usage, and responsible data handling throughout the AI lifecycle.
Program Objectives
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To build foundational GDPR literacy across AI-focused teams
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To apply privacy and security principles in everyday AI development
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To align organizational AI strategies with regulatory and ethical standards
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To promote transparency, accountability, and trust in AI adoption
Program Structure
Week 1: Foundations of Data Privacy and Regulation
Module 1: Understanding GDPR in the AI Context
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Chapter 1.1: Introduction to GDPR – Principles and Scope
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Chapter 1.2: Key Terms: Personal Data, Processing, Consent, Controller vs. Processor
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Chapter 1.3: Relevance of GDPR for AI and ML Projects
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Chapter 1.4: Territorial Scope and Extra-EU Impact
Module 2: Core Privacy Principles and Team Responsibilities
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Chapter 2.1: Data Minimization, Purpose Limitation, and Storage Limitation
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Chapter 2.2: Transparency, Fairness, and Accountability in AI Systems
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Chapter 2.3: Privacy by Design and by Default
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Chapter 2.4: Roles of Engineers, Analysts, Product Managers, and Legal Teams
Week 2: Working Safely with Data in AI Workflows
Module 3: Collecting, Storing, and Using Data
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Chapter 3.1: Lawful Bases for Processing Data (Consent, Contract, Legitimate Interest)
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Chapter 3.2: Anonymization vs. Pseudonymization in AI Projects
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Chapter 3.3: Data Subject Rights (Access, Erasure, Portability, Objection)
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Chapter 3.4: Using External Datasets and Data Sharing Agreements
Module 4: Risk Mitigation and Governance
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Chapter 4.1: Data Protection Impact Assessments (DPIAs) for AI Use Cases
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Chapter 4.2: Vendor Risk Management and Due Diligence
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Chapter 4.3: Security Measures: Encryption, Access Controls, Logging
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Chapter 4.4: Internal Audits and Record-Keeping for AI Models
Week 3: Compliance in Practice and Team Collaboration
Module 5: AI System Design and Auditability
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Chapter 5.1: Building Traceable and Explainable AI Models
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Chapter 5.2: Human-in-the-Loop and Review Mechanisms
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Chapter 5.3: Consent Management and Logging User Interaction
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Chapter 5.4: Aligning Model Deployment with Privacy Controls
Module 6: Preparing for Audits and Regulatory Expectations
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Chapter 6.1: Documenting AI Workflows and Privacy Justifications
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Chapter 6.2: Handling Data Breaches and Regulatory Reporting
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Chapter 6.3: Case Studies: GDPR Violations in AI Products
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Chapter 6.4: Building a Culture of Data Privacy in Cross-Functional Teams
Who Should Enrol?
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Product managers, engineers, data scientists, legal & compliance professionals
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Teams working on AI/ML, data platforms, analytics, or digital products
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No prior legal background required
Program Outcomes
By the end of this course, teams will:
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Understand the impact of GDPR on AI development and deployment
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Apply privacy-by-design strategies to AI workflows and products
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Communicate more effectively across technical and compliance teams
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Reduce risk of regulatory breaches and reputational damage
Fee Structure
Discounted: ₹21499 | $249
We accept 20+ global currencies. View list →
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- One-on-one project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
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