Earn 40 CPE Course Credits
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Learners Count
90,000+ Learners

Program Highlights

InfosecTrain's Certified AI-Powered SOC Analyst program equips learners with the skills needed for next-generation SOC operations. The course blends SOC fundamentals, threat intelligence, AI-driven log analysis, automated alert triage, AI-assisted incident response, and hands-on security tooling across modern enterprise environments. Learners gain a deep understanding of how AI improves detection accuracy and reduces SOC workload through intelligent automation.

40-Hour Instructor-led Training
SOC Fundamentals → AI for Cybersecurity → SIEM & Threat Detection
Hands-on Labs: Log Analysis, Threat Intel, Malware & IR using AI
AI-driven Alert Classification & Anomaly Detection
Real-world SOC Case Studies & Attack Simulations
Exposure to SIEM, EDR & Open-source LLM Models
Mentoring and Post-Training Support
Access to Recorded Sessions
Training Schedule
Start Date End Date Start/End Time Batch Type Training Mode Batch Status
11-Jul-2026 05-Sep-2026 19:00 - 23:00 (IST) Weekend Online [ Open ] Enroll
26-Sep-2026 15-Nov-2026 09:00 - 13:00 (IST) Weekend Online [ Open ] Enroll

About Course

InfosecTrain's Certified AI-Powered SOC Analyst course teaches participants how modern SOCs leverage AI to speed detection, reduce false positives, perform automated investigation, and improve response accuracy. The program explains SOC functions, network security foundations, threat intelligence, log analysis, vulnerability assessment, phishing & malware detection, and AI-driven incident response. Participants gain practical experience through guided labs using SIEM tools, AI models, and real security datasets.

Course Curriculum

MODULE 1

Introduction to SOC

  • What is a SOC?
    • Definition, role in cybersecurity defense
    • SOC structures: Centralized, Distributed, Virtual SOCs
  • SOC Analyst Roles
    • L1: Monitoring, triage, escalation
    • L2 & L3: Deep investigation, threat hunting, forensics
  • Key SOC Functions
    • Log monitoring, alert triage, threat detection, incident response
  • SOC Maturity Model
    • From reactive → proactive → predictive SOC
  • Common SOC Tools
    • SIEM, EDR, Threat Intel Platforms, Open-Source Security Analyst oriented models
MODULE 2

Introduction to AI for Cybersecurity

  • What is AI?
    • AI vs ML vs DL vs NLP vs LLM
    • Predictive AI vs Generative AI
  • Why AI in Cybersecurity?
    • Reducing false positives, handling large datasets, automated response
  • AI in SOC - Use Cases
    • Log summarization, phishing detection, anomaly detection
    • AI-driven report generation, automated playbooks
  • AI Limitations in SOC
    • Hallucinations, bias, explainability, data privacy concerns
  • Open-Source and Free-Tier AI Tools
    • Free Tier proprietary LLMs, Ollama, LMStudio, Hugging Face models
  • Lab:
    • Run an LLM locally (Phi-3 Mini / Mistral via Ollama) → ask it to summarize sample Windows Event logs and classify alerts.
    • MODULE 3

    Network Security & Threat Landscape

    • Basics of Networking for SOC
      • OSI model, TCP/IP, ports & protocols
      • Common attacks (DDoS, brute force, phishing, ransomware)
      • Case studies of famous attacks
    • Threat Intelligence
      • Threat intelligence types
      • IOC (Indicators of Compromise)
      • MITRE ATT&CK for SOC Analysts
    • AI in Threat Intel
      • Using AI to summarize threat feeds
      • AI-assisted correlation of IOCs
  • Lab:
    • Gathering Threat Intel feeds using AI.
    • Capture sample PCAP in Wireshark → use Python + AI model to identify anomalies
    • MODULE 4

    AI in Vulnerability Management & Assessment

    • Vulnerability Management Basics
      • What is a vulnerability? CVE, CVSS, exploitability
      • VM lifecycle: Scan → Assess → Prioritize → Remediate → Report
      • Tools overview: Nessus (pro), OpenVAS (free), Nmap + NSE scripts
      • SOC Analyst role vs. vulnerability management team
    • AI in Vulnerability Assessment
      • AI for CVE explanation: simplify technical CVEs into analyst-friendly notes
      • AI for prioritization: map severity + exploitability + asset criticality
      • AI for remediation recommendations: patch, config change, or mitigation
      • AI in report drafting for management/non-technical audience
  • Lab:
    • OpenVAS/NMAP Scan + AI Explanation
    • AI-Generated Vulnerability Report
    • MODULE 5

    SIEM & AI-Assisted Log Analysis

    • SIEM Fundamentals
      • Architecture, log sources, parsing, correlation rules
      • Popular tools: Splunk, ELK
    • Challenges in Log Analysis
      • High volume, repetitive patterns
    • AI Integration
      • AI for log summarization and anomaly detection
      • ChatGPT prompt engineering for SIEM queries
      • AI-driven "Explain this log" and "Generate query"
  • Lab:
    • AI-powered analysis of Windows Event Logs (4624, 4625, 4670, etc.)
    • Using AI to generate Splunk queries and summarize alerts
    • Parse Suricate logs to elk via filebeat and use AI model to detect network Attack (Malicious Log detector to generate alerts)
    • MODULE 6

    Phishing, Malware, and Insider Threats

    • Phishing
      • Types (email, smishing, vishing, spear phishing, whaling)
      • Real case studies (Norfund, Colonial Pipeline)
    • Malware
      • Introduction to Malware
      • Types of Malware
      • Malware Family Naming
      • Behavioral detection vs signature-based detection
    • Insider Threats
      • Privilege misuse, data exfiltration patterns
    • AI in Detection
      • AI-based phishing email detection
      • AI chatbot for suspicious email reporting
      • AI in malware recognition
  • Lab:
    • AI-based phishing email classification
    • AI for static malware analysis
    • MODULE 7

    Incident Response with AI

    • IR Lifecycle
      • Preparation → Detection → Containment → Eradication → Recovery → Lessons Learned
    • AI in IR
      • AI-guided playbooks
      • Automating IOC enrichment (IP/URL/domain lookups)
      • AI-assisted RCA (Root Cause Analysis)
  • Lab:
    • Using AI to Assist in Phishing Incident Response
    • Network Traffic Analysis using Wireshark + AI

    • Target Audience

    • Aspiring SOC Analysts (L1)
    • Cybersecurity beginners entering SOC roles and aiming to use AI tools effectively
    • Junior Security Analysts working with logs and alerts
    • IT professionals transitioning into SOC operations
    • Fresh graduates aiming for entry-level SOC positions

    Pre-requisites

    • Basic understanding of networking & cybersecurity fundamentals
    • Familiarity with Windows/Linux basics
    • No prior SOC or AI experience required

    Course Objectives

    • Build foundational SOC analysis skills with AI
    • Use AI for alert triage, log summaries and investigations
    • Detect phishing, malware and anomalies with AI support
    • Automate vulnerability reporting and IOC enrichment
    • Assist in IR workflows using AI models
    • Enhance SOC productivity with AI-driven tools
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    Benefits of InfosecTrain's Certified AI-Powered SOC Analyst Training
    Learn AI-enhanced SOC workflows for modern detection needs
    Gain hands-on experience with SIEM, AI models and real datasets
    Improve threat detection accuracy with AI-Driven Automation
    Build confidence for SOC analyst (L1/L2) roles
    Reduce alert fatigue through AI-driven triage and intelligent automation
    Average Salary
    $ 145,000
    $ 120,000
    $ 130,000
    $ 125,000
    $ 110,000
    SOC Analyst
    (AI-Enabled)
    Threat Detection
    Engineer
    AI Cybersecurity
    Analyst
    Security Operations
    Specialist
    AI Incident Response
    Analyst
    Hiring Companies
    Accenture Amazon Web Services (AWS) Deloitte Ernst & Young (EY) Google IBM Microsoft
    Source: Glassdoor, PayScale, Indeed
    Confused about choosing the right course?
    How We Help You Succeed
    Vision Vision
    Goal Goal
    Skill Building Skill-Building
    Mentoring Mentoring
    Direction Direction
    Support Support
    Success Success
    Our Expert Course Advisors
    SANYAM NEGI
    10+ Years of Experience
    CEH | CSA | CND | CHFI | CTIA | CCISO | SOC | Security + | Pentest + | Cysa +
    Sanyam is a cybersecurity expert with 10+ years of experience in Web Application Security, Advanced Penetration Testing, Threat Hunting, and SOC Enablement. He has conducted red-teaming engagements, vulnerability assessments, and forensic investigations. With expertise in DevSecOps implementation and cybersecurity architecture design, he has supported organizations across Linux, Windows, AWS, OVH, and Google Cloud. Sanyam also develops technical training content to enhance cybersecurity team capabilities and operational effectiveness.
    Words Have Power
    Waseem Akram Fareed
    Canada
    I have pursued CISSP, CRISC, and CISM from InfosecTrain. InfosecTrain is my default option when I think about any cybersecurity certification. The trainer's dedication and sincerity towards his classes is something that inspires me a lot personally. You will get 100 percent from InfosecTrain for whichever course you want to pursue. Especially the trainers are outstanding.
    Fuzail Ahmed Lohare
    UAE
    The trainer was very good, with good knowledge and skills to share, and he handled the session with patience. I really enjoyed the training. Selecting InfosecTrain is always a good choice for me. The sales team is very supportive and helped me on this journey.
    Rudraram Sai Kiran
    United Kingdom
    The trainer is a great presenter/tutor and teaches in a relaxing manner. His sense of humor and honesty about the task ahead for the newbie help make the challenging subject matter accessible. Thank you very much! I had been looking forward to this workshop for weeks, and it exceeded my expectations! I have learned a lot.
    Jatin Tandon
    Canada
    Very detailed and organized training, as always, by the best instructors at InfosecTrain. Will come back for more courses after completing my certification.
    Yamna Taouss
    Morocco
    It was an interesting training that could help me succeed in obtaining certificates. I am truly thankful to InfosecTrain for an amazing training. Looking forward to attending more sessions with InfosecTrain.
    Why Choose Infosec Train?

    Learn from certified trainers & industry experts

    Practice with labs, regular assessments, and case studies

    Immerse with scenario-based learning across APT domains

    Best Quality Training with Best Price Guarantee

    Prepare to excel with mock tests, exam tips, and real-world examples

    Conquer the world of Penetration Testing

    Updated curriculum aligned with the latest Pentesting tools

    Choose Flexible Learning options including weekend batches

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    Frequently Asked Questions
    An AI-powered SOC analyst is a security professional who leverages AI-driven log analysis, anomaly detection, automated alert triage, and AI-assisted incident response to improve detection accuracy, reduce false positives, and enhance SOC productivity.
    AI improves threat detection by analyzing large log datasets, identifying anomalies, correlating IOCs, summarizing alerts, detecting phishing and malware patterns, and supporting automated investigation to enhance detection accuracy and reduce false positives.
    Yes, the course covers SIEM fundamentals, including Splunk and ELK, log parsing, correlation rules, AI-powered log summarization, anomaly detection, and generating SIEM queries using AI-driven workflows.
    Yes, the program includes AI-guided playbooks, automated IOC enrichment, AI-driven report generation, and automated response workflows as part of AI-assisted incident response and SOC operations.
    This certification is designed for aspiring SOC analysts, junior security analysts, cybersecurity beginners entering SOC roles, IT professionals transitioning into SOC operations, and fresh graduates seeking entry-level SOC positions.
    Yes, the course aligns with SOC analyst roles, including L1 responsibilities like monitoring and triage, and L2 functions such as deeper investigation and threat analysis enhanced through AI-driven tools.
    Yes, the program includes hands-on labs covering AI-powered log analysis, vulnerability assessment, phishing detection, malware analysis, incident response workflows, and threat intelligence using SIEM tools and AI models.
    Yes, AI reduces alert fatigue by summarizing logs, automating triage, prioritizing alerts, detecting anomalies, reducing false positives, and assisting analysts with intelligent investigation workflows.
    The certification prepares learners for SOC roles powered by AI-driven detection and automation, including entry-level SOC analyst positions and junior security analyst roles in modern enterprise security environments.
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