Empower Your Team—Build AI Responsibly with Data Privacy by Design.
“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.
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.
To build foundational GDPR literacy across AI-focused teams
To apply privacy and security principles in everyday AI development
To align organizational AI strategies with regulatory and ethical standards
To promote transparency, accountability, and trust in AI adoption
Week 1: Foundations of Data Privacy and Regulation
Module 1: Understanding GDPR in the AI Context
Chapter 1.1: Introduction to GDPR – Principles and Scope
Chapter 1.2: Key Terms: Personal Data, Processing, Consent, Controller vs. Processor
Chapter 1.3: Relevance of GDPR for AI and ML Projects
Chapter 1.4: Territorial Scope and Extra-EU Impact
Module 2: Core Privacy Principles and Team Responsibilities
Chapter 2.1: Data Minimization, Purpose Limitation, and Storage Limitation
Chapter 2.2: Transparency, Fairness, and Accountability in AI Systems
Chapter 2.3: Privacy by Design and by Default
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
Chapter 3.1: Lawful Bases for Processing Data (Consent, Contract, Legitimate Interest)
Chapter 3.2: Anonymization vs. Pseudonymization in AI Projects
Chapter 3.3: Data Subject Rights (Access, Erasure, Portability, Objection)
Chapter 3.4: Using External Datasets and Data Sharing Agreements
Module 4: Risk Mitigation and Governance
Chapter 4.1: Data Protection Impact Assessments (DPIAs) for AI Use Cases
Chapter 4.2: Vendor Risk Management and Due Diligence
Chapter 4.3: Security Measures: Encryption, Access Controls, Logging
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
Chapter 5.1: Building Traceable and Explainable AI Models
Chapter 5.2: Human-in-the-Loop and Review Mechanisms
Chapter 5.3: Consent Management and Logging User Interaction
Chapter 5.4: Aligning Model Deployment with Privacy Controls
Module 6: Preparing for Audits and Regulatory Expectations
Chapter 6.1: Documenting AI Workflows and Privacy Justifications
Chapter 6.2: Handling Data Breaches and Regulatory Reporting
Chapter 6.3: Case Studies: GDPR Violations in AI Products
Chapter 6.4: Building a Culture of Data Privacy in Cross-Functional Teams
Product managers, engineers, data scientists, legal & compliance professionals
Teams working on AI/ML, data platforms, analytics, or digital products
No prior legal background required
By the end of this course, teams will:
Understand the impact of GDPR on AI development and deployment
Apply privacy-by-design strategies to AI workflows and products
Communicate more effectively across technical and compliance teams
Reduce risk of regulatory breaches and reputational damage
Discounted: ₹21499 | $249
We accept 20+ global currencies. View list →
Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).
Watch the recording in your dashboard and send your questions to the mentor through the support desk.
Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.
Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.
By card, UPI or PayPal on the payment page; international bank transfer is also available there.
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