Data Privacy Concepts and Techniques

  • Overview
  • Course Content
  • Requirements & Materials
Overview

Data Privacy Concepts and Techniques

Course Description

This course explores data privacy through the lens of Artificial Intelligence, linking core principles to cutting-edge practice. After tracing two decades of privacy evolution — and why legacy safeguards fail against AI-driven data mining — participants will examine modern privacy-enhancing technologies that enable responsible AI. This includes federated learning, secure multi-party computation, and differential privacy. Learners unpack the technical and mathematical guarantees behind these tools and analyze real-world deployments that protect sensitive data while still fueling AI innovation.

Course Content
  • History of data privacy techniques and how the privacy landscape evolved over the past 20 years
  • Conceptual and technical aspects of data privacy
  • Past failures of previous privacy techniques
  • Current state-of-the-art privacy techniques, such as federated learning, secure aggregation, and differential privacy
  • Mathematical and technical underpinnings of current techniques
  • Real-life uses and applications of current privacy techniques
Requirements & Materials

Prerequisites

RECOMMENDED:

Undergraduate-level mathematics with a grasp of calculus and basic probability concepts.

Materials

PROVIDED (Student will receive):

  • "Differential Privacy: Overview and Fundamental Techniques'' by N. Fioretto, P.V. Hentenryck, and J. Ziani.
  • Research articles on data privacy

Who Should Attend

Professionals interested in developing state-of-the-art technical and mathematical data privacy skills. It's open to anyone wanting to understand the importance of data privacy, the gap between state-of-the-art privacy techniques, and the practical implementation of privacy. Data privacy officers, data scientists, machine learning engineers, software engineers, cybersecurity analysts, and researchers will benefit.

Business professional attending in-person professional development course

What You Will Learn

  • Definition of data privacy, how the privacy landscape changed over the past 20 years, and reasons that older techniques like anonymization are now insufficient
  • Effects to online data, including potential harms and systematic impacts
  • Core concepts associated with the different regulatory frameworks for privacy
  • Potential applications of technical and mathematical tools to promote and guarantee privacy
Defense tech professional attending a short course

How You Will Benefit

  • Gain perspectives on how to conceptualize data privacy both in your personal life and within the context of the professional world and research.
  • Understand current mathematical approaches to bolster data privacy.
  • Appreciate how state-of-the-art data privacy technologies can help guarantee data privacy.
  • Grow Your Professional Network icon
    Grow Your Professional Network
  • Taught by Experts in the Field icon
    Taught by Experts in the Field

TRAIN AT YOUR LOCATION

We enable employers to provide specialized, on-location training on their own timetables. Our world-renowned experts can create unique content that meets your employees' specific needs. We also have the ability to deliver courses via web conferencing or on-demand online videos. For 15 or more students, it is more cost-effective for us to come to you.

  • Save Money
  • Flexible Schedule
  • Group Training
  • Customize Content
  • On-Site Training
  • Earn a Certificate
Learn More

Want to learn more about this course?