GDPR & AI Data Privacy for Teams
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Course Overview
Table of Contents
Program Syllabus
Module 1
About
“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.
Module 2
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.
Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Limited SeatsClosing Soon
GDPR & AI Data Privacy for Teams
Professional Certification Program
🎥
FormatLive + Recorded
📅
Duration8 Weeks
📜
CertificationVerified
Module 3
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
Module 4
Program Structure
Module 5
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 6
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
Module 7
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 8
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
Module 9
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 10
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
Module 11
Video Module TOC
~7 hours of video content aligned with weekly modules
Module 12
Week 1 Videos
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Introduction to GDPR: Scope, Goals, and Principles
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Key Concepts: Personal Data, Consent, Controllers, and Processors
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Why GDPR Matters for AI and Machine Learning
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Cross-Border Data Flow and Territorial Scope
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Core Privacy Principles in Practice: Minimization and Limitation
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Transparency, Fairness, and Human Rights in AI
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Privacy by Design: Integrating from Day One
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Roles and Responsibilities Across Data Teams
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Week 1 Recap and Team Reflection Activity
Module 13
Week 2 Videos
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Lawful Bases for Processing in AI Projects
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Handling Consent: Opt-ins, Records, and Withdrawal
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Pseudonymization vs. Anonymization Explained
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Data Subject Rights: Access, Deletion, and Objection
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Working with External or Public Datasets under GDPR
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Conducting a DPIA for an AI Model
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Managing Third-Party Vendors and Subprocessors
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Implementing Security: Encryption, Monitoring, and Logs
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Week 2 Compliance Scenario Review
Module 14
Week 3 Videos
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Designing Auditable and Transparent AI Systems
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Explainability in Practice: Techniques for ML Teams
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Human-in-the-Loop for Sensitive AI Decisions
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Logging and Consent Management in Real Applications
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Preparing for Privacy Audits and Regulator Inquiries
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Incident Response and Breach Notification Essentials
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Case Studies: What Went Wrong (GDPR Enforcement in AI)
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Team Culture and Ethical Decision Making
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Final Project Briefing and Course Wrap-Up
Module 15
Live Lecture Module
Live sessions to align legal, technical, and operational perspectives on AI data privacy
Module 16
Lecture 1 (Week 1)
Title: Understanding GDPR Through the AI Lens: What Every Team Member Should Know
Duration: 60 minutes
Focus: Introduction to GDPR essentials and how they map to roles in AI and product teams
Guest: Privacy Lawyer or Data Protection Officer
Interactive: Live role-mapping activity + real-time quiz on core GDPR principles
Module 17
Lecture 2 (Week 2)
Title: Data in Practice: From Collection to Modeling with Privacy in Mind
Duration: 75 minutes
Focus: How teams can apply GDPR during dataset creation, AI development, and vendor selection
Guest: AI Data Governance Lead or Privacy-by-Design Consultant
Interactive: Case walkthrough of a privacy checklist during AI model setup + DPIA workshop
Module 18
Lecture 3 (Week 3)
Title: Operationalizing Compliance: Embedding Data Privacy into AI Workflows
Duration: 90 minutes
Focus: Audit-readiness, documentation standards, and building a privacy-first team culture
Guest Panel: AI Product Manager + Security Architect + Regulator or Auditor
Interactive: Live audit simulation + open team discussion on privacy pitfalls and resolutions
Module 19
Intended For
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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
Module 20
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
Module 22
Fee Structure
Fee: INR 21499 USD 249
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of CurrenciesModule 23
FOR QUERIES, FEEDBACK OR ASSISTANCE
Module 24
Key Takeaways
- Access to e-LMS
- Real Time Project for Dissertation
- Project Guidance
- Paper Publication Opportunity
- Self Assessment
- Final Examination
- e-Certification
- e-Marksheet
Module 25
Future Career Prospects
Learners will strengthen their team’s capacity to:
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Build and manage GDPR-compliant AI systems
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Design privacy-aware features in digital products
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Coordinate with legal teams on AI compliance
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Support roles in PrivacyOps, Data Ethics, and Responsible AI
Module 26
Job Opportunities
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AI Product Manager (Privacy-Aware)
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Compliance Officer (AI Projects)
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Responsible AI Specialist
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Privacy Consultant for Tech Teams
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Data Protection Lead (AI Solutions)
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Legal-Tech Risk Analyst
Module 27
Enter the Hall of Fame!
Take your research to the next level!
Publication Opportunity
Potentially earn a place in our coveted Hall of Fame.
Centre of Excellence
Join the esteemed Centre of Excellence.
Networking and Learning
Network with industry leaders, access ongoing learning opportunities.
Hall of Fame
Get your groundbreaking work considered for publication in a prestigious Open Access Journal (worth ₹20,000/USD 1,000).
Achieve excellence and solidify your reputation among the elite!
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Module 28
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