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Network Automation with AI

Course Code:

Détails du cours

Description

Key Topics Covered

  • Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and SLA performance across network domains
  • Telemetry and real-time observability, covering data collection from multi-domain sources, streaming analytics, and integration with assurance systems
  • Analytics and decision-making frameworks, including rule-based and AI-driven policy engines for SLA monitoring, predictive analysis, and automated decision triggers
  • Automated orchestration and remediation actions, enabling scaling, rerouting, reconfiguration, and fault recovery across RAN, Core, Transport, and Cloud
  • End-to-end service assurance integration, including KPI monitoring, SLA enforcement, incident automation, and alignment with operational processes

Learning Outcomes

  • Apply closed‑loop automation frameworks (monitor → analyse → decide → act)
  • Identify relevant telemetry/KPI sources for real‑time decisions
  • Explain interplay between analytics engines and orchestration layers
  • Understand assisted vs full closed‑loop implementation models."

Target Audience

  • Network automation engineers
  • AI/analytics engineers supporting network assurance
  • OSS platform architects
    Operations teams responsible for service assurance and performance

Détails du cours

Fiche produit

Key Topics Covered Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and... En savoir plus

Schedule Closed Course

Duration:
Price: £POA (up to 12 Delegates)

Chaque cours comprend :

  • Livré par des experts en la matière possédant des décennies d'expérience dans l'industrie.
  • Disponible pour livraison en classe ou via une classe virtuelle
  • La classe virtuelle propose la même expérience d'apprentissage interactive et engageante que la formation en classe en face à face.
  • Disponible sous forme de programme de formation fermé en entreprise. Envoyez un e-mail à info@wraycastle.com pour plus d'informations.

Description

Key Topics Covered

  • Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and SLA performance across network domains
  • Telemetry and real-time observability, covering data collection from multi-domain sources, streaming analytics, and integration with assurance systems
  • Analytics and decision-making frameworks, including rule-based and AI-driven policy engines for SLA monitoring, predictive analysis, and automated decision triggers
  • Automated orchestration and remediation actions, enabling scaling, rerouting, reconfiguration, and fault recovery across RAN, Core, Transport, and Cloud
  • End-to-end service assurance integration, including KPI monitoring, SLA enforcement, incident automation, and alignment with operational processes

Learning Outcomes

  • Apply closed‑loop automation frameworks (monitor → analyse → decide → act)
  • Identify relevant telemetry/KPI sources for real‑time decisions
  • Explain interplay between analytics engines and orchestration layers
  • Understand assisted vs full closed‑loop implementation models."

Target Audience

  • Network automation engineers
  • AI/analytics engineers supporting network assurance
  • OSS platform architects
    Operations teams responsible for service assurance and performance

Nos clients et partenaires

  • UIC Rail Academy
  • IEEE
  • TCCA
  • UKTIN
  • DB
  • Scotish Fire
  • MTN
  • All Points Fibre
  • Department of Defence

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