Pideya Learning Academy

Smart SOC Operations Powered by AI

Upcoming Schedules

  • Schedule

Date Venue Duration Fee (USD)
24 Feb - 28 Feb 2025 Live Online 5 Day 3250
17 Mar - 21 Mar 2025 Live Online 5 Day 3250
07 Apr - 11 Apr 2025 Live Online 5 Day 3250
09 Jun - 13 Jun 2025 Live Online 5 Day 3250
07 Jul - 11 Jul 2025 Live Online 5 Day 3250
08 Sep - 12 Sep 2025 Live Online 5 Day 3250
20 Oct - 24 Oct 2025 Live Online 5 Day 3250
24 Nov - 28 Nov 2025 Live Online 5 Day 3250

Course Overview

As the digital threat landscape continues to evolve at an unprecedented pace, Security Operations Centers (SOCs) are facing mounting challenges in keeping up with increasingly sophisticated cyber threats. Traditional SOC architectures—built on static rules, manual triage, and reactive response protocols—are no longer sufficient in safeguarding dynamic enterprise networks. Recognizing this critical shift, Pideya Learning Academy presents Smart SOC Operations Powered by AI, a forward-looking training program designed to reshape SOC strategies through artificial intelligence, intelligent automation, and machine learning integration.
AI-powered SOCs represent a transformative leap from conventional operations by enabling faster, more accurate threat detection and resolution. According to IBM’s Cost of a Data Breach Report 2024, organizations that had fully deployed security AI and automation reported an average of $1.76 million lower breach costs compared to those without. Additionally, Gartner projects that by 2026, over 60% of large enterprises will have integrated AI-enhanced SOC workflows to reduce alert fatigue and streamline decision-making. These statistics clearly underscore the growing reliance on AI to elevate cybersecurity readiness and operational agility.
This immersive course equips participants with the knowledge and frameworks to redesign their SOC ecosystems, enabling real-time detection, intelligent alert triaging, and automated response. Participants will gain actionable insights on embedding AI capabilities across SIEM, SOAR, and EDR platforms, while also understanding how to balance innovation with governance, compliance, and ethical implementation. Core areas of focus throughout the training include:
Understanding the fundamentals of AI-driven SOC architecture and threat intelligence frameworks
Designing automated triage and incident escalation workflows using AI and ML models
Leveraging behavioral analytics to detect anomalies, zero-day attacks, and advanced persistent threats
Exploring machine learning applications in SOC alert classification and event correlation
Reducing false positives through AI-based alert scoring, improving analyst efficiency and focus
Architecting scalable SOC strategies that integrate seamlessly with existing enterprise infrastructure
Evaluating governance, auditability, and ethical considerations in AI-enabled security environments
By integrating these capabilities, Smart SOC Operations Powered by AI offers a comprehensive learning journey—from strategic planning to technical implementation. The program delves into the role of Natural Language Processing in enhancing alert context, predictive modeling in proactive threat response, and adaptive analytics in threat hunting.
Whether building a new SOC or evolving an existing one, this course serves as a vital resource for cybersecurity professionals aiming to future-proof their operations. Through its well-structured modules, the course ensures that participants can move from conceptual understanding to strategic application, ready to lead security innovation within their organizations. By fostering a deeper understanding of intelligent automation in cybersecurity, Pideya Learning Academy empowers participants to design resilient, efficient, and AI-driven security frameworks that stand at the forefront of digital defense.

Course Objectives

After completing this Pideya Learning Academy training, the participants will learn to:
Define the core components of an AI-augmented SOC framework
Evaluate the limitations of conventional SOC operations and the value of AI integration
Implement machine learning models for intelligent log analysis and threat hunting
Design automated incident response strategies using AI and SOAR platforms
Align AI-driven SOC strategies with organizational risk tolerance and governance models
Leverage advanced analytics for behavioral threat detection and triage optimization
Build adaptive response mechanisms to dynamic and evolving threat landscapes
Integrate AI with SIEM tools to enhance real-time alert correlation
Establish metrics and KPIs for continuous improvement of SOC operations
Address ethical, compliance, and bias considerations in AI-driven security solutions

Personal Benefits

Deep expertise in next-generation SOC operations powered by AI and automation
Capability to design intelligent security workflows and detection models
Competitive advantage in cybersecurity leadership and career progression
Enhanced ability to interpret AI analytics for strategic threat mitigation
Mastery over emerging technologies shaping the future of SOC environments

Organisational Benefits

Accelerated threat detection and response time through AI-driven automation
Improved SOC team efficiency and reduced alert fatigue
Enhanced cyber resilience and readiness for zero-day threats
Optimized resource utilization through intelligent workload allocation
Alignment of SOC strategies with digital transformation and enterprise agility
Strengthened compliance with cybersecurity standards and frameworks

Who Should Attend

SOC Analysts and Managers
Cybersecurity Engineers and Architects
IT Security and Infrastructure Professionals
Threat Intelligence Specialists
SIEM/SOAR Platform Administrators
CISO Office and Cybersecurity Strategists
Digital Transformation Leads in Security Functions
Detailed Training

Course Outline

Module 1: Foundations of Smart SOC Operations
Evolution of SOC Models AI vs Traditional Threat Detection Modern Threat Landscape SOC Maturity Models Key Roles in a Smart SOC AI Readiness Assessment SOC Framework Standards (NIST, MITRE ATT&CK)
Module 2: AI Fundamentals in Cybersecurity
AI and ML Terminology Supervised vs Unsupervised Learning AI in Log Analysis Neural Networks for Security Natural Language Processing Use Cases Reinforcement Learning in SOC AI Model Training & Tuning
Module 3: Data Architecture for AI-Powered SOCs
Data Ingestion Pipelines Log Normalization and Parsing Data Quality in Threat Detection Data Lake vs SIEM Integration Real-time Stream Processing Privacy and Data Governance Structured vs Unstructured Data Use
Module 4: Threat Intelligence Integration
External Threat Feeds Threat Intelligence Platforms (TIPs) Indicator of Compromise (IoC) Correlation AI-Powered Threat Classification Behavioral Profiling Threat Actor Attribution Predictive Threat Modelling
Module 5: Intelligent Alert Management
Alert Volume Challenges AI-Based Alert Scoring Prioritization Logic with ML Reducing False Positives NLP in Alert Description Parsing Escalation Protocols with Automation Continuous Alert Tuning
Module 6: Automated Incident Response
SOAR Fundamentals Playbook Orchestration with AI Auto-Ticketing and Assignment Response Decision Trees Workflow Triggering Logic Post-Incident Analysis with AI SLA Monitoring and Compliance
Module 7: Behavioral Analytics and Anomaly Detection
User and Entity Behavior Analytics (UEBA) Insider Threat Detection Anomaly Baselines AI for Pattern Deviation Zero-Day Attack Visibility Integration with Endpoint Detection Identity Analytics for SOC
Module 8: Advanced Analytics for SOC Optimization
Security Data Visualization Predictive Dashboards AI-Driven KPI Reporting Root Cause Analysis with ML Capacity Planning Models SOC Efficiency Scoring Alert Heatmaps
Module 9: Governance, Ethics, and Explainability
AI Auditability Requirements Bias in Threat Models Ethical SOC Automation Regulatory Alignment (GDPR, ISO) Transparent Model Decisions Risk Scoring Ethics Explainable AI (XAI) in SOC
Module 10: Building a Future-Ready AI SOC Strategy
SOC Roadmapping Techniques Budgeting for AI Integration Cloud-native SOC Strategies Vendor Evaluation and Toolchain Selection Hybrid and Multi-cloud Security Upskilling for AI SOC Teams Measuring Strategic Impact

Have Any Question?

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