TELCOMA Certified AI for Telecom Networks Specialist

What's assessed

6 domains, 42 questions in total — drawn from the course lessons.

• The AI toolbox, in network terms

  7 questions

  Placing AI in the network you already run: where it already lives, what model, training and inference actually mean, what networks log as counters, KPIs and traces, and when a threshold beats a model.

• Machine learning through telecom cases

  7 questions

  The core ML families taught on real network problems: supervised traffic prediction, unsupervised anomaly detection, precision and recall against the cost of a false alarm, drift, and when deep learning is genuinely needed.

• GenAI and LLMs in operations

  7 questions

  Where large language models help in network operations and where they do not, judged by what the work actually needs rather than by what the technology can be made to do.

• NWDAF and the network's own data pipeline

  7 questions

  The analytics function the standard already defines: what NWDAF collects, the analytics it exposes, and how the network's own data pipeline feeds decisions rather than dashboards.

• From SON to closed-loop automation

  7 questions

  Connecting the SON automation you already own to closed-loop, intent-driven operation — observe, decide, act and who approves; explainability and rollback; and what changes when the loop is the design.

• Trust, governance and your first deployment

  7 questions

  The judgment layer: accountable AI with explainability, bias and an audit trail; securing models against poisoning, theft and adversarial input; build versus buy; and picking a first deployment that cannot hurt you.