GDPR for Beginners

Inter and intra-company training

Level reached

Advanced

Duration

 2,00 day(s)

Language(s) of service

EN

Who is organizing this training?

Explore the future of tech learning with Devseis - Luxembourg’s dynamic and accredited training partner. We deliver hands-on, career-focused programs in Software and Web Development, Mobile App Development, Cloud and DevOps, Data Privacy and GDPR Compliance, Digital Marketing, and Machine Learning with a focus on EU AI Act readiness. Our approach combines real-world projects, expert mentorship, and a learner-centric philosophy to ensure every participant gains not just knowledge, but the confidence to apply it. Train for impact. Grow with confidence. Learn with Devseis.

Who is the training for?

This training is designed for professionals who need a practical, real-world understanding of GDPR and the EU AI Act, and who want to integrate modern AI-assisted tools into their compliance work. It is suitable for:

  • Beginners Welcome (from any sector and domain)
  • Compliance, Legal & Governance Professionals
  • IT, Data & Technical Teams
  • HR, Operations & Administrative Roles
  • AI, Innovation & Digital Transformation Roles
  • Public Sector, NGOs & Education

Goals

By the end of this training, participants will be able to:

  • Understand the legal foundations of GDPR by interpreting core principles (Art. 5) and real court rulings and decisions from data protection authorities.
  • Identify and classify personal data — including special category and mixed data — using practical examples and legal definitions (Art. 4, 9).
  • Apply data subject rights in practice (Art. 12–23) by drafting access, rectification, and erasure responses using AI-supported templates and real case examples.
  • Differentiate the roles and responsibilities of data controllers, processors, and Data Protection Officers (DPOs), and understand liability and accountability mechanisms (Art. 24–28, 37).
  • Build a GDPR-compliant Record of Processing Activities (RoPA) for a fictional organisation, covering data types, purposes, legal bases, transfers, and retention (Art. 30).
  • Conduct a personal data risk assessment based on the RoPA and map the risks to appropriate legal, technical, and organisational safeguards (Art. 32, 35).
  • Simulate a GDPR-style internal audit using real-world checklists, reporting structures, and team-based scenarios modelled after DPA expectations.
  • Leverage AI tools responsibly to draft privacy policies, DPIA summaries, data handling procedures, and data subject request replies while maintaining human oversight.

Contents

Module 1: GDPR Principles in Action

What you’ll learn:

  • The 7 core GDPR principles (Art. 5)
  • Real cases demonstrating breaches and how authorities enforced them

Hands-on:

  • Analyse 3 short case summaries (e.g., H&M, Google Spain, Clearview AI)
  • Match each principle to the facts
  • Use AI to paraphrase legalese into plain language explanations

Module 2: Personal, Special & Mixed Data – What You Hold and How You Handle It

What you’ll learn:

  • Art. 4 definitions of personal, special category, and mixed personal data
  • How to distinguish facts from opinion in performance reviews, HR records, etc.

Hands-on:

  • Review 5 anonymised data samples
  • Use AI to classify each one and suggest legal bases for processing
  • *

Module 3: Rights of the Data Subject

What you’ll learn:

  • Overview of Art. 12–23: access, rectification, erasure, objection, portability
  • When and how rights apply, with real enforcement examples

Hands-on:

  • Use templates + AI to draft:
    • Access request reply
    • Erasure confirmation
    • Rectification notice

Module 4: Roles & Responsibilities – Controller, Processor, DPO

What you’ll learn:

  • Art. 24–28 obligations
  • What regulators look for in DPOs, contracts, and processor accountability

Hands-on:

  • Work in pairs to assign responsibilities in a real scenario (e.g., a SaaS company using external HR tools)
  • Use AI to review contract clauses and flag missing elements

Module 5: Build Your GDPR Register (RoPA)

What you’ll learn:

  • Art. 30 register requirements
  • How to document data subjects, purposes, legal bases, transfers, and retention

Hands-on:

  • Use AI-assisted templates to build a RoPA for a fictional company
  • Peer review another group’s RoPA for completeness and clarity

Module 6: Risk Assessment, Safeguards, & AI Governance

What you’ll learn:

  • How to conduct a basic risk analysis
  • Choosing proportionate safeguards (Art. 32, 35)
  • When to perform a DPIA to identify risks.
  • Manage high risks in compliance with EU-AI Act

Hands-on:

  • Identify 3–5 risks in your RoPA
  • Use AI to suggest suitable technical, legal, and organisational controls

Module 7: GDPR Audit Simulation

What you’ll learn:

  • Internal audit structure: scope, findings, remediation
  • Common findings in supervisory authority audits

Hands-on:

  • Simulate a DPO-style audit of your fictional organisation:
    • Check data flows
    • Review documentation
    • Issue a mock audit report using templates

Module 8: Draft Key GDPR Documents with AI

What you’ll learn:

  • AI-assisted policy generation: privacy notice, internal policy, DPIA summary
  • Ensuring human oversight and GDPR-compliant outputs

Hands-on:

  • Feed your RoPA or scenario into AI tools
  • Draft:
    • Privacy notice
    • Data retention policy
    • DPIA summary
    • Subject Access Request (SAR) response
  • Review outputs for compliance and clarity

Points covered

  • Key GDPR and EU AI Act concepts decoded using real-life court cases and enforcement actions from Data Protection Authorities.
  • Identification and handling of different data types: personal, special category, and mixed personal data.
  • Breakdown of all data subject rights (Art. 12–23) with practical, real-world examples and template-based exercises.
  • Roles, responsibilities, and liability mapping for controllers, processors, and DPOs — including joint and third-party processing cases.
  • Live, guided creation of a GDPR Record of Processing Activities (RoPA) from a fictional organisational context.
  • A simple framework for personal data risk assessment, connected to appropriate safeguards and DPIA triggers.
  • Use of checklists and audit tools to simulate a GDPR internal audit with peer review and role-based tasks.
  • Introduction to AI-assisted compliance writing, including privacy notices, SAR responses, and internal data protection policies.
  • Ready-to-use templates, AI prompt libraries, register samples, and compliance checklists for real-world deployment post-training.

Teaching methods

Methodology based on Active Learning: 50% minimum practice. Each theoretical point is systematically followed by examples and exercises.

Evaluation

  • Participants will complete small, practical assignments after each module.
  • Progress will be continuously monitored through quick tasks and feedback.
  • There will be no heavy exams - just simple hands-on practice to build confidence.

Certificate, diploma

Certificate of completion