COURSE

IOTA5204

Distributed and Federated Machine Learning

Information Hub / Internet of Things · 3 Credits

This course examines the theory, systems, and applications of machine learning in distributed, edge, and federated environments. Students will learn foundational methods in machine learning as well as the relevant statistics and mathematics. They will explore the architectures and communication patterns of distributed training, and study the challenges unique to federated settings, such as privacy, heterogeneity, and resource constraints. Emphasis is placed on practical systems and real-world use-cases, culminating in a project where students design and implement a distributed or federated learning solution.