Edge AI for 5G & 6G Applications
Target Audience
Researchers, Industry Professionals, Advanced Faculty
Duration
5 Hours
Mode of Delivery
Hybrid
Overview
This session covers the convergence of edge computing and AI for ultra-low latency applications in 5G/6G. Participants will explore distributed intelligence for IoT, autonomous vehicles, and real-time analytics.
Detailed Topics & Subtopics:
- Edge AI Basics & Architectures (30 mins)
- AI Models Deployment at Edge Nodes (45 mins)
- 5G MEC (Multi-access Edge Computing) Use Cases (40 mins)
- 6G Vision: Distributed Intelligence (30 mins)
- Hands-on: Deploying a Lightweight AI Model on Edge (80 mins)
- Case Studies: Autonomous Systems, Smart Cities (45 mins)
- Open Q&A (30 mins)
Learning Outcomes
- Deploy AI models in edge environments.
- Understand MEC’s role in 5G/6G ecosystems
- Explore 6G’s AI-native distributed intelligence vision
Further Learning
- Edge AI certifications, OpenNESS/EdgeX Foundry tools.
Frequently Asked Questions (FAQs)
Anyone interested in learning how AI can be applied to 5G networks — including students, faculty, researchers, and professionals.
A general interest in technology is enough. Some basic knowledge of networks or AI is helpful, but not mandatory.
It will be delivered in hybrid mode - you can attend either online or on-site.
The total course duration is just 5 hours, delivered through live online sessions.
You’ll learn how AI is being used in modern networks, explore real-world examples, and get hands-on experience with basic tools and datasets