AI for Telecom Training
Build a clear, practical understanding of how artificial intelligence can transform telecom networks — from planning and optimization to automation and decision-making — responsibly and at scale.
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Flexible duration Executive briefing (1 Day) or 2-4 days in-depth training
Practical and applied Real telecom use cases, governance frameworks, and decision-ready tools
Designed for telecom leaders Delivered to CTO, network, architecture, and transformation teams
What this training delivers
- AI fundamentals tailored to telecom networks (ML, GenAI, automation, decision support)
- High-impact use cases across RAN, Core, Transport, and Network Operations (planning, optimization, assurance)
- Data & analytics foundations: KPIs, logs, traces, feature engineering, and model evaluation for network environments
- Governance and risk management: explainability, bias, privacy, security, and operational accountability
- From PoC to scale: industrialization, MLOps lifecycle, operating model, and ROI-driven prioritization
Training modules
AI Foundations for Telecom
Understand AI, machine learning, and generative AI in the context of telecom networks. Learn what AI can and cannot do, how models are trained and evaluated, and how to avoid common pitfalls in network deployments.
AI Use Cases in RAN (Planning & Optimization)
Capacity forecasting, smart planning, traffic prediction, parameter tuning, energy optimization, and anomaly detection. Understand how AI supports RAN operations and where human validation remains critical.
AI in Core, Services & Customer Experience
AI-driven insights for signaling analytics, service assurance, VoLTE/VoNR experience, churn drivers, and QoE/QoS correlation. Learn how to translate network data into customer-impact and business priorities.
Network Automation, Assurance & Closed-Loop Operations
Closed-loop automation concepts, intent-based operations, AI-assisted troubleshooting, and root cause analysis. How to design guardrails and success metrics to automate safely and reliably.
From Pilot to Scale (Industrialization & MLOps)
How to move from experimentation to production: data readiness, model lifecycle (train/deploy/monitor), integration into OSS/BSS and workflows, vendor strategy, and ROI-based roadmap.
Who should attend
- CTO office, Technology & Network Strategy teams
- Network Architecture (RAN / Core / Transport) and Engineering teams
- Radio Optimization & Performance teams
- NOC / Service Assurance / Operations & Automation teams
- Innovation, Transformation, and Data/Analytics leaders
