This course focuses on computing at the network edge to enable low-latency, real-time, and bandwidth-efficient applications. It covers edge AI, distributed intelligence, security, and edge–cloud integration for IoT, automotive, and industrial systems.
Fundamental Topics
Covers edge computing concepts, architectures, edge devices, data processing basics, latency reduction, and cloud integration.
Edge vs cloud computing
Embedded processors
Communication protocols
Intermediate Topics
Focuses on edge analytics, distributed computing, IoT integration, security challenges, orchestration, and real-time processing techniques.
Edge AI
Resource optimization
Security at edge
Advanced Topics
Includes AI at edge, autonomous systems, edge-cloud collaboration, scalability, advanced security, optimization, and future architectures.
Federated learning
Real-time analytics
Edge-cloud orchestration
Course Outcomes
Enable students to design, deploy, and manage efficient edge computing solutions for real-time applications.