AI and ML are now core to modern network operations. This chapter explains the difference between generative and predictive AI, where each shows up in netops today (assistants, anomaly detection, capacity forecasting, ChatOps), and the limits you need to understand.
| Type | What it does | Netops example |
|---|---|---|
| Predictive AI / ML | Learns patterns from historical telemetry and predicts or classifies new data points | Anomaly detection on flow logs, traffic forecasting, root-cause clustering, malware classification |
| Generative AI | Produces new text/code/diagrams by sampling a large language model | Drafting CLI configs, summarising 'show tech-support', writing runbook docs, ChatOps assistants |
2 more sections in this chapter, plus a 2-question quiz.
You can see the title, summary, learning objectives and the opening sections. The rest of this chapter, like all of modules 2–8, comes with the Course & Lab Pass and All-Access Max. A free account opens Module 1: Network Foundations end-to-end and saves your labs — start there, no card required.
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