AI in 5G Networks: Deployment Aspects, Risks and Telecom LLM

AI in Telecom - AI/ML adoption, LLM for 5G networks, on-device / cloud LLM and 5G AI challenges

AI adoption in 5G networks is already a reality!

I give you 3 hours of well-structured video presentations in simple words when I will help you to gain a competitive knowledge to be ahead of everybody in AI adoption.

Doesn't mean who you are: CEO, CTO, PhD student or 5G engineer this course provides a full overview of AI and Machine Learning implementation aspects in 5G networks that you will use in your telecom company.

By the end of this course, you'll understand:

• Basic AI/ML concepts related to telecom networks, including Generative AI, Large Language Models (LLMs), and Federated Learning.

• Challenges and solutions for implementing Generative AI in 5G mobile networks.

• The potential of LLMs in telecom areas, such as on-demand LLM and 5G Multi-Edge Computing (MEC).

• 5G infrastructure challenges and key performance indicators (KPIs) related to AI implementation.

• Ethical and privacy considerations specific to AI in the telecom industry.

  
  

Additionally, the course covers:

• AI for network optimization and traffic management.

• AI-based network security measures.

• AI in network slicing and 5G standalone architecture.

• Regulatory aspects and future trends, including the transition to 6G networks.

• The current market landscape of AI and LLM in telecom, including open-source options and potential use cases in 5G networks.

You will have a possibility to check your knowledge after each paragraph.

This course is designed for anyone curious about AI implementation in mobile networks.

Let's rock telecom together!