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Udemy

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

via Udemy

Overview

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

What you'll learn:
  • Understand AI/ML basics for Mobile Networks
  • Identify the aspects of AI deployment in Telecom
  • Examine the challenges and solutions for Generative AI (LLMs) adoption in Telecom
  • Gain in-depth knowledge about Telecom LLMs and such aspects as on-device LLMs / proprietary and open-source LLM

AI adoption in 5G networks is already a reality!


This is not another surface-level “AI for telecom” overview.

I give you 5.5 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.


The only course where 5G engineers, CTOs, and telecom researchers get the complete picture — standards, deployment realities, LLM economics, and the roadmap to 6G AI-native architecture. No hype. No marketing.


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

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

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

  • The truth about on‑device LLM inference, semantic communication, and the coming 10x uplink explosion driven by AI+AR devices (or not?).

  • 5G infrastructure challenges and KPIs related to AI features and implementation.

  • How AI‑driven beam management, CSI feedback, and UEpositioning are being standardized in 3GPP - and what you already can implement right now.

  • Why AI‑native air interfaces and deep neural receivers will soon replace conventional RF blocks - and how to prepare?


But we also confront the uncomfortable truths:

  • Why most AI “solutions” will never reach production - and how to spot them.

  • The hidden TCO of AI‑infrastructure, model generalization gaps, and control‑layer risks.

  • How AI traffic will break current QoS models and force to re‑engineer our telecom networks.

  • The ethical, privacy, and workforce upheavals that come with true AI adoption.

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


Let's rock telecom together!

Syllabus

  • AI fundamentals: terminology and challenges
  • AI adoption for Telecom: from challenges to solutions
  • LLMs in Telecom: models, costs, infrastructure, KPIs, optimization.
  • AI/ML features in 5G 3GPP networks

Taught by

Gleb Marchenko

Reviews

4.3 rating at Udemy based on 107 ratings

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