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$20

AI Network Operations Assistant

Build a carrier-grade AIOps system: ingest network topology, alarms, and KPI time-series; build a topology graph; correlate an alarm storm down to its root-cause element; predict outages from leading indicators; and ship an agent that assembles each incident, proposes a root cause and remediation, and drafts the RCA behind a human approval gate — never auto-remediating. Recall-first: capture every real incident, then cut alarm noise.

"One fiber cut lit up 200 alarms — pinpoint the root cause and flag the sites about to go down"

6 Interactive Sessions

Short, interactive sessions: watch it work, try it, then build it yourself. You can go deeper at any time in the written chapters.

  1. 1

    One cut fibre, a screen full of alarms

    Before the system can find what broke, it has to load four kinds of data and check that every row joins up. A row that does not join is an incident nobody will see.

  2. 2

    The network map: what depends on what

    Build the network map so that, for any element, you can answer two questions at once: what depends on this, and what does this depend on?

  3. 3

    Many alarms, one cause: catch every incident first

    Group the alarm flood into incidents, name the one element whose failure explains each one, and cut the noise, but only after every real incident has been caught.

  4. 4

    See the outage coming

    Learn what normal looks like for each element, flag it when it drifts, and for faults that build up slowly, warn before the promised limit is broken, with time to act.

  5. 5

    The agent drafts, a person decides

    Let an AI agent do the gathering and the first drafts, so the engineer spends their time on judgment, and put a person in front of every change to the network.

  6. 6

    A NOC someone can run, and an auditor can follow

    Put a screen on the pipeline that an engineer can work from, measure it with the four numbers that show whether the NOC is healthy, and make every incident and every action traceable.

Skills you'll practise

Data PipelineTopology GraphAlarm CorrelationRoot-Cause AnalysisOutage PredictionHuman-in-the-Loop Agent

Practice data included

  • Network topology & inventory
  • Alarm event stream (72h)
  • KPI time-series (latency · loss · throughput)
  • Trouble & change tickets
  • Labeled incidents (fiber cut · power · congestion)

How this certificate is scored

Your certificate shows how many of your written answers met the rubric below, checked by an AI grader. Anyone who checks your certificate sees it.

  • You answer 6 short questions, one for each module, in your own words (at least 40 words each).
  • An AI grader checks each answer against what its module asks for: it must answer the question, use the course's practice case specifically, and be correct.
  • To pass, at least 5 of the 6 answers must meet that bar. The certificate says the answers were graded by AI.

The rubric

  1. Module 1, Ingest: Topology + alarm + KPI + ticket data model & loaders.
  2. Module 2, Topology: Network topology graph + downstream impact.
  3. Module 3, Correlate: Alarm-storm correlation + topology-aware root cause.
  4. Module 4, Detect & Predict: KPI anomaly + outage prediction with lead-time.
  5. Module 5, Triage Agent: Incident-triage agent that drafts an RCA (human-approved).
  6. Module 6, Deploy: NOC console + monitoring dashboard (MTTR, noise, SLA).

What you walk away with

Shareable portfolio

A public URL showing your module timeline, patterns mastered, and completion status.

Everything you build

Download all your work as a ZIP file. It is yours to keep.

Module walkthrough

Each module documented with deliverables and the production pattern you implemented.

Ready to start AI Network Operations Assistant?

First course free. $20 per course after that.