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TUTBB · Sep 26, 2026

AI for Telecom Networks ML, GenAI & NWDAF in Operations
Published 9/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 48m | Size: 2.05 GB
How AI really works in telecom operations: machine learning on network data, LLMs in operations, NWDAF, closed loops

What you'll learn
Place AI in a network you already know: what it does today and why data quality decides everything
Explain supervised and unsupervised learning, evaluation and model drift through real network problems
Say what large language models genuinely do in network operations, and how their failure modes are contained
Describe NWDAF, the 5G core's analytics function: one analytics round trip, training versus serving, and its siblings
Connect SON to closed-loop, intent-driven automation, and decide who approves what
Apply accountable AI, protect the models themselves, and make the build-versus-buy call
Choose a first AI deployment in the network that cannot hurt you
Requirements
Recommended: 5G Foundation, or general familiarity with how a mobile network works
No coding or maths background required
Description
This course contains the use of artificial intelligence.There is no shortage of AI claims in telecom. What is harder to find is a clear account of what actually runs in networks today, what is still a pilot, and how to tell the difference. This course gives you that, using problems a network team already recognises.
By the end you can explain the core machine learning methods through real network cases, say where large language models genuinely help an operations team, describe how the 5G core's own analytics function works, and choose a first AI deployment that is safe to run.
What the 6 sections cover
-The AI toolbox, in network terms
-Machine learning through telecom cases
-GenAI and LLMs in operations
-NWDAF and the network's own data pipeline
-From SON to closed-loop automation
-Trust, governance and your first deployment
How it is taught
26 video lessons, about 3.8 hours in total, most between five and nine minutes. Every lesson is built around one idea and one diagram that you watch being assembled, with the real terms attached once the picture makes sense. Short on-screen checks let you test yourself as you go; they are for your own practice, not a grade. The first section is free to preview.
Background: Recommended: 5G Foundation, or general familiarity with how a mobile network is built. No prior AI knowledge needed.
Who it suits: network operations and NOC engineers, planning and optimisation engineers, telecom managers evaluating AI projects, and data people moving into telecom.
This course is independent training. It is not affiliated with or endorsed by 3GPP, ETSI or any AI vendor. Names of organisations and specifications are used only to describe the technology.
Who this course is for
Network operations and NOC engineers
Planning and optimisation engineers
Telecom managers evaluating AI projects
Data scientists and analysts moving into telecom
Homepage

Code:

https://www.udemy.com/course/ai-for-telecom-networks/

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AI for Telecom Networks ML, GenAI & NWDAF in Operations

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