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Network Automation with AI

Course Code:

Kurs Detayları

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

Kurs Detayları

Product form

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

Schedule Closed Course

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

Her Kursun Özellikleri:

  • Sektörde onlarca yıllık deneyime sahip konu uzmanları tarafından sunulur.
  • Sınıfta veya sanal sınıf aracılığıyla teslim edilebilir
  • Sanal Sınıf, yüz yüze sınıf eğitimiyle aynı etkileşimli, ilgi çekici öğrenme deneyimini sunar.
  • Kapalı şirket içi eğitim programı olarak mevcuttur. Daha fazla bilgi için info@wraycastle.com adresine e-posta gönderin.

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

Müşterilerimiz ve Ortaklarımız

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

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