Get in Touch
 Duration 21 hours

Course Outline

Introduction to 5G and Edge AI

  • Overview of 5G networks and edge computing
  • Distinct advantages of 5G over 4G for AI applications
  • Challenges and prospects in ultra-low latency AI

5G Architecture and Edge Computing

  • Comprehending 5G network slicing for AI workloads
  • The significance of Multi-Access Edge Computing (MEC)
  • Strategies for deploying Edge AI in telecom settings

Deploying AI Models on Edge Devices with 5G

  • Leveraging TensorFlow Lite and OpenVINO for Edge AI
  • Fine-tuning AI models for real-time processing
  • Case study: AI-driven video analytics over 5G

Ultra-Low Latency Applications Powered by 5G

  • Autonomous vehicles and intelligent transport systems
  • AI-based predictive maintenance in industrial contexts
  • Medical applications: remote diagnostics and continuous monitoring

Security and Reliability in 5G Edge AI Systems

  • Data privacy and cybersecurity issues in 5G AI
  • Maintaining AI model robustness in real-time scenarios
  • Regulatory adherence for AI-enhanced telecom solutions

Future Trends in 5G and Edge AI

  • Progress in 6G and AI-driven networking
  • Combining federated learning with 5G AI
  • Emerging applications in smart cities and IoT

Conclusion and Pathways Forward

Requirements

  • Foundational knowledge of 5G network architecture
  • Familiarity with AI and machine learning principles
  • Practical experience with edge computing and IoT applications

Target Audience

  • Telecom professionals
  • AI engineers
  • IoT specialists

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories