Privacy-Enhancing Technologies (PETs) Courses and Certifications

Google TechTalks

The Data Minimization Principle in Machine Learning

Explore data minimization in machine learning, its challenges, and practical implementations. Examine optimization-based formalization and applications in high-stakes domains, revealing insights on privacy and efficiency.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Google TechTalks

Differentially Private Sampling from Distributions - Google Algorithms Seminar

Explore private sampling from distributions, examining dataset size requirements for various distribution families and comparing private sampling to non-private learning in different parameter regimes.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Security BSides San Francisco

F-ck These Guys - Practical Counter Surveillance

Practical strategies for protecting online privacy and resisting mass surveillance through encryption and privacy technologies. Learn to safeguard your digital rights and opt out of bulk data collection.

• YouTube
• 45 minutes
• Self-Paced
• Conference Talk

GOTO Conferences

Practical Data Privacy

Explore practical data privacy implementation with open-source libraries, privacy-enhancing technologies, and strategies for balancing privacy and utility in software development and data science projects.

• YouTube
• 39 minutes
• Self-Paced
• Conference Talk

EuroPython Conference

PySyft: Data Science on Data You Are Not Allowed to See

Explore PySyft for secure data science collaboration, enabling privacy-preserving analysis on sensitive datasets without direct access. Learn to implement machine learning with robust privacy guarantees.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

EuroPython Conference

Encrypted Computing in Python Using OpenFHE

Explore Fully Homomorphic Encryption (FHE) and its applications in privacy-preserving machine learning. Learn to use OpenFHE's Python interface for encrypted computing, with practical examples and concepts.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Conf42

Zenroom: Cryptographic VM for Blockchain Interoperability

Explore Zenroom, a cryptographic VM for blockchain interoperability, and its applications in Web 3.0 technologies.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

MLOps World: Machine Learning in Production

MLOps on Highly Sensitive Data - Enhancing Security and Compliance

Enhance security and compliance in MLOps for sensitive data using Kubernetes, blockchain tokenization, and confidential computing. Learn from a life sciences case study.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

Drupal Association

Designing for Privacy: Balancing User Needs and Data Security

Explore strategies for designing privacy-focused UX, balancing user needs with data security. Learn to identify risks, communicate effectively, and implement privacy-enhancing technologies in digital experiences.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Machine Learning with Sensitive Data: Privacy-Preserving Techniques

Explore open-source ML techniques for sensitive data in finance and healthcare, ensuring privacy while maximizing data utility.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Federated Learning: Unlocking the Value of Distributed Data

Explore federated learning to leverage distributed data for robust machine learning models without centralizing sensitive information. Learn benefits, challenges, and practical applications.

• YouTube
• 1 hour 35 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

ML-Based Privacy-Preserving Framework for Generating Synthetic Data from Aggregated Sources

Explore a multi-stage framework for generating synthetic data from aggregated sources, focusing on downscaling techniques and real-world applications in data privacy and model performance improvement.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

Navigating the Tradeoff Between Privacy and Fairness in Machine Learning

Explore the intersection of privacy and fairness in ML, addressing challenges and research-based solutions for regulated industries.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Toronto Machine Learning Series (TMLS)

The Latest Advances in Privacy-Preserving NLP

Explore cutting-edge privacy-preserving NLP techniques, including differential privacy, pseudonymization, and homomorphic encryption. Gain insights into protecting sensitive data in natural language processing applications.

• YouTube
• 19 minutes
• Self-Paced
• Free Video

All Things Open

Jurity: State-of-the-Art Open Source Software for AI Fairness Evaluation

Explore Jurity, an open-source tool for AI fairness evaluation without collecting personal data. Learn about state-of-the-art methods and opportunities in fairness testing for AI models.

• YouTube
• 24 minutes
• Self-Paced
• Free Video