The Advanced Workshop on Secure AI Protocols is designed to equip participants with cutting-edge skills in federated learning, focusing on secure and privacy-preserving AI methods. This hands-on workshop emphasizes project-based learning, allowing attendees to engage in real-world applications while collaborating with peers. Participants will explore the latest techniques in secure AI protocols, gaining practical insights that can be immediately applied in their professional environments.
Throughout the course, learners will work on projects that culminate in the publication of their findings in Cademix Magazine, providing an opportunity to share their expertise with a wider audience. The workshop’s interactive format fosters a dynamic learning atmosphere, encouraging participants to think critically and creatively about the challenges and solutions in the realm of secure AI. By the end of the program, attendees will have a comprehensive understanding of federated learning and its implementation in secure AI systems.
Introduction to Federated Learning Concepts
Overview of Secure AI Protocols
Techniques for Data Privacy in AI
Implementing Federated Learning Frameworks
Secure Multi-Party Computation Basics
Differential Privacy in Federated Learning
Case Studies of Secure AI Applications
Hands-on Project: Developing a Secure AI Model
Strategies for Collaboration in Federated Learning
Final Project Presentation and Publication Preparation