AI-RAN & the AI-Native Network

Open with the radio's real tension, re-teach the air-interface and RAN-compute frames a Foundation-only learner needs, and lock the three-strand discipline.

4 lessons · 1 checkpoint · ≈26 min

Exactly the ML mechanics the rest of the course spends — fitted functions, time-series prediction, one-sided vs two-sided models, life-cycle management and fallback discipline — all through radio data.

5 lessons · 1 lab · ≈32 min

The 3GPP strand with exact provenance — the frozen one-sided framework and its three use cases, the life-cycle signalling, and the two-sided story told at its true status.

6 lessons · 1 lab · ≈42 min

Deepen the two-clock picture into working knowledge — loop budgets, the named wires, where models are trained and shipped, and a scorecard moved honestly forward.

5 lessons · 1 checkpoint · ≈29 min

Cash the shared-compute promise honestly — the three prepositions, what running the physical layer on accelerated compute takes, what has genuinely run versus been announced, the open silicon debate, and the economics.

6 lessons · 1 lab · ≈48 min

The network-side 3GPP track that went normative a release earlier, sleep mechanics and honest per-denominator savings, the three operating models that run production RAN AI, and a truthful cash-out of "AI-native".

5 lessons · 1 checkpoint · ≈39 min