Federated Learning and Privacy-Aware AI for IoT Networks Training from Tonex, Inc.

Federated Learning and Privacy-Aware AI for IoT Networks Training

Online, Self-Paced

Protect privacy in smart ecosystems with "Federated Learning and Privacy-Aware AI for IoT Networks Training." Learn how distributed learning enables secure AI training without compromising sensitive user data.

Learning Objectives

Understand the principles of federated learning and privacy-aware AI.
Analyze how federated learning can be used to train AI models on distributed data.
Evaluate the benefits of privacy-aware AI for IoT networks.
Identify best practices for building secure and privacy-preserving AI systems.
Discuss the challenges and opportunities of implementing federated learning in IoT environments.

Framework Connections

Protection and Defense

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Competency Areas

Work Roles

Feedback

If you would like to provide feedback on this course, please e-mail the NICCS team at NICCS@mail.cisa.dhs.gov. Please keep in mind that NICCS does not own this course or accept payment for course entry. If you have questions related to the details of this course, such as cost, prerequisites, how to register, etc., please contact the course training provider directly. You can find course training provider contact information by following the link that says “Visit course page for more information...” on this page.