Hardware-Networking
AI for Network Monitoring and Troubleshooting
This practical course helps professionals master AI for network monitoring, anomaly detection, root cause support, ticket enrichment, and troubleshooting workflows. The program connects key concepts, real use cases, risks, tools, and operational decisions so participants can apply the learning in their work environment. It can be tailored to the organization’s sector, internal systems, participant maturity, and performance objectives.
Objectives
- Understand the concepts, challenges, and use cases related to AI for network monitoring, anomaly detection, root cause support, ticket enrichment, and troubleshooting workflows.
- Identify the data, systems, processes, and stakeholders required for effective implementation.
- Assess risks, limitations, governance requirements, and practical control points.
- Use methods, tools, and templates to structure analysis and decision-making.
- Translate learning into action plans, recommendations, and measurable improvement opportunities.
- Adapt the approach to the operating context, team maturity, and business objectives.
Target audience
- Network, systems, and infrastructure administrators
- Support technicians and IT engineers
- Data center, endpoint, and operations teams
- Professionals preparing for networking certifications
- IT managers responsible for availability and resilience
Program outline
A clear structure for the learning journey.
Outline points are grouped in one designed block instead of being treated as separate module cards.
01Network Monitoring Data, Telemetry, Logs, and Events4 topics
- Foundation for Network Monitoring Data, Telemetry, Logs, and Events: application, analysis, and review points linked to the module
- Terminology and decisions in Network Monitoring Data, Telemetry, Logs, and Events: application, analysis, and review points linked to the module
- Inputs required for Network Monitoring Data, Telemetry, Logs, and Events: application, analysis, and review points linked to the module
- Typical mistakes around Network Monitoring Data, Telemetry, Logs, and Events: applied exercise and practical decision from a realistic scenario
02AI Use Cases for Anomaly Detection and Incident Reduction4 topics
- Current-state mapping for AI Use Cases for Anomaly Detection and Incident Reduction: application, analysis, and review points linked to the module
- Examples and scenarios involving AI Use Cases for Anomaly Detection and Incident Reduction: application, analysis, and review points linked to the module
- Diagnostic questions about AI Use Cases for Anomaly Detection and Incident Reduction: application, analysis, and review points linked to the module
- Evidence produced through AI Use Cases for Anomaly Detection and Incident Reduction: applied exercise and practical decision from a realistic scenario
03Baselines, Thresholds, Seasonality, and Noise Reduction4 topics
- Design considerations for Baselines, Thresholds, Seasonality, and Noise Reduction: application, analysis, and review points linked to the module
- Roles and responsibilities in Baselines, Thresholds, Seasonality, and Noise Reduction: application, analysis, and review points linked to the module
- Exceptions and constraints affecting Baselines, Thresholds, Seasonality, and Noise Reduction: application, analysis, and review points linked to the module
- Quality checks for Baselines, Thresholds, Seasonality, and Noise Reduction: applied exercise and practical decision from a realistic scenario
04Root Cause Support, Correlation, and Dependency Mapping4 topics
- Operating model for Root Cause Support, Correlation, and Dependency Mapping: application, analysis, and review points linked to the module
- Tools and workflow steps in Root Cause Support, Correlation, and Dependency Mapping: application, analysis, and review points linked to the module
- Handoffs and approvals around Root Cause Support, Correlation, and Dependency Mapping: application, analysis, and review points linked to the module
- Escalation points in Root Cause Support, Correlation, and Dependency Mapping: applied exercise and practical decision from a realistic scenario
05Ticket Enrichment, Suggested Actions, and Human Review4 topics
- Performance measures for Ticket Enrichment, Suggested Actions, and Human Review: application, analysis, and review points linked to the module
- Review routines after Ticket Enrichment, Suggested Actions, and Human Review: application, analysis, and review points linked to the module
- Improvement actions for Ticket Enrichment, Suggested Actions, and Human Review: application, analysis, and review points linked to the module
- Sustaining discipline around Ticket Enrichment, Suggested Actions, and Human Review: applied exercise and practical decision from a realistic scenario
06Integration with NMS, SIEM, ITSM, and Observability Tools4 topics
- Advanced scenarios in Integration with NMS, SIEM, ITSM, and Observability Tools: application, analysis, and review points linked to the module
- Failure patterns seen in Integration with NMS, SIEM, ITSM, and Observability Tools: application, analysis, and review points linked to the module
- Coordination challenges during Integration with NMS, SIEM, ITSM, and Observability Tools: application, analysis, and review points linked to the module
- Recovery actions for Integration with NMS, SIEM, ITSM, and Observability Tools: applied exercise and practical decision from a realistic scenario
07Model Quality, False Positives, Governance, and Adoption4 topics
- Governance requirements for Model Quality, False Positives, Governance, and Adoption: application, analysis, and review points linked to the module
- Data quality checks in Model Quality, False Positives, Governance, and Adoption: application, analysis, and review points linked to the module
- Risk controls related to Model Quality, False Positives, Governance, and Adoption: application, analysis, and review points linked to the module
- Value measures for Model Quality, False Positives, Governance, and Adoption: applied exercise and practical decision from a realistic scenario
08AI Network Monitoring Use Case Workshop4 topics
- Implementation planning for AI Network Monitoring Use Case Workshop: application, analysis, and review points linked to the module
- Readiness questions before AI Network Monitoring Use Case Workshop: application, analysis, and review points linked to the module
- Pilot design for AI Network Monitoring Use Case Workshop: application, analysis, and review points linked to the module
- Lessons learned after AI Network Monitoring Use Case Workshop: applied exercise and practical decision from a realistic scenario
Materials provided
- ○ Slides used during the sessions
- ○ Group activities and practical exercises
- ○ Worksheets, checklists, and templates
- ○ Case studies relevant to the course
- ○ 4D Certificate of Completion issued by 4D Training & Consultancy
- ○ Post-course support for technical queries and guidance
Training Options
Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.
Why choose 4D
4D Training & Consultancy designs technical and professional programs around the client’s operating reality. The course can be adapted to sector requirements, internal systems, team capability, practical use cases, and the level of depth required by the audience.
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