AI, Data & Automation in Telecom

Explore our comprehensive AI, Data & Automation in Telecom training programs in Courses for Government, Regulatory & Public Sector Technology Programs.

Responsible AI, Ethics & Explainability for Public Sector Telecom Use

As telecom authorities and public sector organizations increasingly adopt AI for spectrum management, QoS monitoring, fraud detection, network automation, and policy analytics, ensuring that these systems are ethical, transparent, fair, secure, and accountable is critical. Unlike commercial deployments, public sector AI systems must withstand legal scrutiny, public trust requirements, and auditability expectations. This course provides a comprehensive understanding of Responsible AI principles, focusing on ethics, explainability (XAI), governance frameworks, risk management, and regulatory alignment in telecom use cases. Participants will learn how to evaluate, govern, and operationalize AI systems responsibly across the telecom domain.

5 Days

Machine Learning for Network Analytics & Predictive Operations

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.

5 Days

Intelligent OSS/BSS & Automation Using AI

Modern telecom networks (4G/5G, cloud-native cores, private networks) generate massive operational data across OSS (Operations Support Systems) and BSS (Business Support Systems). Traditional rule-based systems struggle with scale, complexity, and real-time responsiveness. Artificial Intelligence (AI) enables intelligent automation, predictive operations, closed-loop assurance, and enhanced customer experience. This course provides a comprehensive understanding of AI-driven OSS/BSS transformation, covering architecture evolution, AI use cases, automation frameworks, analytics integration, and governance. It is designed for telecom authorities, operators, PSUs, and system integrators seeking to modernize operations while ensuring reliability, transparency, and compliance.

5 Days

Data Analytics & Big Data Platforms for Telecom Authorities

Telecom authorities increasingly rely on large-scale data analytics to support policy formulation, spectrum management, QoS compliance, market oversight, security, and public accountability. With data generated from networks, operators, monitoring systems, and citizen feedback, traditional tools are insufficient to extract timely and actionable insights. This course provides an end-to-end understanding of data analytics and big data platforms in the telecom regulatory context, covering data sources, analytics models, big data architectures, governance, and decision-making use cases. Participants will learn how big data platforms are designed, operated, and used responsibly to support evidence-based telecom governance.

5 Days

Artificial Intelligence in Telecom – Concepts, Applications & Governance

Artificial Intelligence (AI) is rapidly transforming telecom networks by enabling automation, predictive analytics, self-optimizing networks, and enhanced customer experience. At the same time, AI introduces new governance challenges related to transparency, accountability, data privacy, security, and regulatory oversight. This course provides an end-to-end understanding of AI in the telecom domain, covering core AI concepts, practical use cases across network layers, and policy & governance frameworks. Participants will learn how AI is applied, evaluated, regulated, and governed within telecom ecosystems, with emphasis on public interest, trust, and responsible deployment.

5 Days

AI for Spectrum Optimization & Interference Detection

With increasing spectrum congestion, dynamic sharing models, and the introduction of 5G, NTN, and private networks, traditional rule-based spectrum monitoring and interference management are no longer sufficient. Artificial Intelligence (AI) enables automated spectrum sensing, anomaly detection, predictive interference analysis, and optimization of spectrum usage. This course provides an end-to-end understanding of how AI can be applied to spectrum management, covering AI fundamentals, spectrum analytics, interference detection techniques, and governance considerations. Participants will learn how AI supports proactive, data-driven spectrum decisions while ensuring regulatory compliance and transparency.

5 Days

AI for Fraud Detection, SIM Abuse & Revenue Protection

Telecom networks face increasing threats from subscription fraud, SIM abuse, revenue leakage, interconnect fraud, and emerging AI-assisted fraud patterns. Traditional rule-based systems are often reactive and insufficient against fast-evolving fraud techniques. Artificial Intelligence (AI) enables early detection, pattern recognition, predictive risk scoring, and automated mitigation across both OSS and BSS domains. This course provides a comprehensive understanding of AI-driven fraud management, covering fraud typologies, data sources, analytics models, operational workflows, and regulatory considerations. Participants will gain the ability to interpret AI-generated insights, design fraud detection frameworks, and support revenue protection initiatives in line with governance and compliance requirements.

5 Days