Course Details
Machine Learning for Network Analytics & Predictive Operations
5 Days
Course Overview
Modern telecom networks generate massive volumes of data from RAN, core, transport, OSS/BSS, and customer experience systems. Traditional rule-based monitoring is no longer sufficient to manage network complexity, scale, and service expectations. This course provides a hands-on, application-oriented introduction to Machine Learning (ML) for network analytics and predictive operations. Participants will learn how ML models are used to detect anomalies, predict faults, forecast demand, and support proactive network operations, enabling the transition toward AIOps and self-healing networks.
Upcoming Trainings
Feb 9, 2026
Hyderabad, India
Feb 23, 2026
Hyderabad, India
Mar 9, 2026
Chennai, India
Mar 23, 2026
Chennai, India
Target Audience
- Telecom network operations (NOC) engineers
- RF, core, and transport network analysts
- OSS/BSS and performance management teams
- Network planning and optimization engineers
- Data analysts working with telecom data
- Technical managers and AIOps program leads
- System integrators and solution architects
Prerequisites
- Basic understanding of telecom network architecture (RAN, Core, Transport)
- Understanding of network KPIs and performance metrics
- Familiarity with basic statistics (mean, variance, correlation)
- Excel or basic scripting concepts (helpful)
- No prior ML or advanced programming experience required (Python exposure beneficial but not mandatory)
Course Outline