AI for Cyber Security : Threat Detection, SOC Automation

Descripción

Artificial Intelligence is redefining the future of cybersecurity — and this course is your complete roadmap to mastering it. In AI for Cybersecurity: Threat Detection & SOC Automation, you’ll learn how AI, Machine Learning (ML), and Deep Learning (DL) are transforming how organisations detect, prevent, and respond to cyber threats. This program blends real-world labs, tools, and automation workflows to prepare you for the next generation of AI-driven cybersecurity roles — from SOC analyst to security automation engineer. What You’ll Learn Across Modules: • Module 1: Introduction to AI in Cybersecurity Learn the foundations of AI, ML, and DL, explore their evolution, benefits, and challenges, and see how AI integrates into real-world SOC environments with tools like Darktrace and CrowdStrike. • Module 2: AI for Threat Detection Understand machine learning for anomaly detection, supervised vs unsupervised learning, and how AI enhances IDS systems like Suricata for faster and smarter threat identification. • Module 3: AI for Threat Intelligence Discover how Natural Language Processing (NLP) is used to analyse phishing data, automate enrichment with APIs such as VirusTotal and AbuseIPDB, and strengthen threat intel pipelines. • Module 4: AI for SOC Automation Explore AI-powered SOAR platforms, playbook automation, and the balance between human and AI decision-making in modern security operations. • Module 5: AI for Incident Response Learn how AI assists in decision-making, predicts breach impact, and optimises real-time alert management and forensic reconstruction. • Module 6: AI for User Behaviour Analytics (UBA) Apply ML models to baseline user activity, detect insider threats, and use graph-based analytics for behavioural risk scoring. • Module 7: AI for Malware Analysis Perform AI-driven malware classification using sandbox analysis, embeddings, and the EMBER dataset to detect and forecast malicious behaviour. • Module 8: AI in Cloud Security Secure cloud environments using AI for misconfiguration detection, anomaly analysis, and posture management with AWS GuardDuty or Azure Defender. • Module 9: AI in Network Security Analyse network traffic, identify DDoS patterns, and apply ML models for encrypted traffic analysis and zero-trust segmentation. • Module 10: AI in Endpoint Security Automate EDR workflows, apply federated learning, and detect ransomware with behaviour-based AI models. • Module 11: Limitations & Ethical Considerations Study bias, false positives, and privacy issues in AI systems to ensure ethical cybersecurity practices. • Module 12: Future of AI in Cybersecurity + Capstone Project Design an AI-augmented SOC workflow, integrating tools, automation, and analytics for intelligent cyber defence. By the end of this course, you’ll be able to build, automate, and manage AI-powered defence systems, preparing you for cutting-edge roles in cybersecurity and AI operations.

Lo que aprenderás

• Students will learn how Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are transforming modern cybersecurity operations.
• Students will gain practical skills to build and apply AI-driven systems for threat detection, SOC automation, and incident response.
• Students will learn how to use popular AI-based cybersecurity tools such as Darktrace, CrowdStrike, and SOAR platforms for automated defense workflows.
• Students will be able to design, simulate, and implement AI-augmented SOC workflows using real-world datasets and automation tools.
• Understand the core principles of Artificial Intelligence and how they apply to cybersecurity.
• Explore real-world use cases of AI in threat detection, malware analysis, and incident response.
• Learn how AI enhances SOC operations, automates tasks, and supports decision-making.
• Identify key risks, challenges, and limitations of using AI in cybersecurity environments.

Requisitos

• A basic understanding of cybersecurity or general IT concepts will be helpful but is not mandatory to start this course.
• No prior experience with AI, machine learning, or programming is required — all essential concepts are explained from scratch.
• Students will need access to a computer with an internet connection to explore hands-on labs, simulations, and AI-powered security tools.
• An eagerness to explore how Artificial Intelligence is revolutionizing cybersecurity and automation will help maximize learning outcomes.