Syllabus

• Week 1

  Foundations of AI-Driven Security Operations

  • Lesson 1: Introduction to Entire Course

    Learn to use AI and Python to automate cybersecurity tasks like threat detection, alert triage, and incident response through hands-on projects.

  • Lesson 2: Foundations of AI-Driven Security Operations

    Explore key SOC challenges like alert fatigue and high data volume, and see how AI automation improves phishing triage, malware analysis, and incident response.

  • Lesson 3: AI Models in Cybersecurity - What You Need to Know

    Understand the differences between ML, DL, and LLMs, and learn how to apply them to anomaly detection, malware classification, and log analysis.

  • Lesson 4: Building Your AI-Powered Security Toolkit

    Set up a Python environment for security automation, integrate AI APIs, and build a simple end-to-end automation pipeline.

• Week 2

  AI-Powered Threat Detection and Analysis

  • Lesson 5: Automated Phishing Detection with AI

    Build automated phishing detection systems by analysing emails, applying ML models, and using AI for advanced threat scoring.

  • Lesson 6: Network Anomaly Detection with Machine Learning

    Detect malicious network activity using ML-based anomaly detection, log analysis, and traffic pattern insights across cloud and on-prem systems.

  • Lesson 7: Malware Analysis and IOC Extraction Automation

    Automate malware analysis and extract IOCs using AI, APIs, and pattern matching to generate actionable threat intelligence.

• Week 3

  Automating Incident Response Workflows

  • Lesson 8: AI-Assisted Alert Triage and Prioritisation

    Automate alert triage by enriching data, applying AI risk analysis, and prioritising threats to reduce false positives and analyst workload.

  • Lesson 9: Automated Investigation and Evidence Collection

    Automate investigations by correlating logs, reconstructing attack timelines, and using AI to identify threats and generate clear reports.

  • Lesson 10: Orchestrating Automated Response Actions

    Automate response actions using APIs to contain threats, block risks, and generate incident tickets with safe, controlled workflows.

• Week 4

  Production-Ready AI Security Automation

  • Lesson 11: Building AI-Powered Security Playbooks with RAG

    Turn static SOPs into AI-driven playbooks using RAG, and build assistants that guide and automate incident response.

  • Lesson 12: End-to-End Autonomous Security Pipelines

    Design event-driven security pipelines for continuous monitoring and automated response with the right balance of human oversight.

  • Lesson 13: Defending Against AI Threats and Future-Proofing

    Understand adversarial AI threats, test and strengthen detection systems, and prepare for future AI-driven cybersecurity challenges.

  • Lesson 14 : Course Conclusion

    Wrap up your learning by reviewing key concepts, reflecting on your automation projects, and preparing to apply AI-driven security workflows in real-world environments.

Who will you learn with?