Course Code: 5gedgeai
Duration: 21 hours
Prerequisites:

  • Basic understanding of 5G network architecture
  • Familiarity with AI and machine learning concepts
  • Experience with edge computing and IoT applications

Audience

  • Telecom professionals
  • AI engineers
  • IoT specialists

Overview:

5G and Edge AI are transforming industries by enabling ultra-low latency applications for real-time decision-making and automation.

This instructor-led, live training (online or onsite) is aimed at intermediate-level telecom professionals, AI engineers, and IoT specialists who wish to explore how 5G networks accelerate Edge AI applications.

By the end of this training, participants will be able to:

  • Understand the fundamentals of 5G technology and its impact on Edge AI.
  • Deploy AI models optimized for low-latency applications in 5G environments.
  • Implement real-time decision-making systems using Edge AI and 5G connectivity.
  • Optimize AI workloads for efficient performance on edge devices.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.

Course Outline:

Introduction to 5G and Edge AI

  • Overview of 5G networks and edge computing
  • Key differences between 4G and 5G for AI applications
  • Challenges and opportunities in ultra-low latency AI

5G Architecture and Edge Computing

  • Understanding 5G network slicing for AI workloads
  • Role of Multi-Access Edge Computing (MEC)
  • Edge AI deployment strategies in telecom environments

Deploying AI Models on Edge Devices with 5G

  • Using TensorFlow Lite and OpenVINO for Edge AI
  • Optimizing AI models for real-time processing
  • Case study: AI-powered video analytics over 5G

Ultra-Low Latency Applications Enabled by 5G

  • Autonomous vehicles and smart transportation
  • AI-driven predictive maintenance in industrial settings
  • Healthcare applications: remote diagnostics and monitoring

Security and Reliability in 5G Edge AI Systems

  • Data privacy and cybersecurity challenges in 5G AI
  • Ensuring AI model robustness in real-time applications
  • Regulatory compliance for AI-powered telecom solutions

Future Trends in 5G and Edge AI

  • Advancements in 6G and AI-driven networking
  • Integration of federated learning with 5G AI
  • Next-generation applications in smart cities and IoT

Summary and Next Steps

Overview in Category:

This instructor-led, live training in <loc> (online or onsite) is aimed at intermediate-level telecom professionals, AI engineers, and IoT specialists who wish to explore how 5G networks accelerate Edge AI applications.

By the end of this training, participants will be able to:

  • Understand the fundamentals of 5G technology and its impact on Edge AI.
  • Deploy AI models optimized for low-latency applications in 5G environments.
  • Implement real-time decision-making systems using Edge AI and 5G connectivity.
  • Optimize AI workloads for efficient performance on edge devices.