This course is part of the Core Cyber Defence & Intelligence Operations ExpertTrack
Core Principles of Using AI Agents in Cyber Defence
Explore how AI agents strengthen SOC operations.

Duration
4 weeksWeekly study
2 hoursIncluded in an ExpertTrack
Course 1 of 4
Core Principles of Using AI Agents in Cyber Defence
This course has been certified by the CPD Certification Service as conforming to continuing professional development principles. Find out more.
Strengthen SOC operations and cyber defence with AI agents
Cyber threats are evolving faster than ever, and security teams need tools to keep pace. AI agents are becoming powerful partners for security teams, helping strengthen detection and response across digital environments. You’ll gain an understanding how they operate is essential for responsible cyber security.
This course guides you through practical ways AI can support modern defense and make daily work more efficient and effective, while keeping human judgement central.
Discover how AI agents strengthen cyber security
AI in security isn’t about replacing teams, it’s about backing them with speed and precision. Agents can scan huge volumes of activity, flag risks sooner, and help teams stay focused on threats that matter.
You’ll explore how AI agents operate, the decisions they support, and the guardrails needed to deploy them responsibly in any security setting.
Investigate threats with AI support
Threats rarely present themselves clearly. They often hide in unusual login patterns, subtle behaviour shifts, or carefully crafted phishing attempts.
Utilising phishing analysis, malware review, and threat intelligence exercises, you’ll see how AI agents highlight risky activity and offer insights that sharpen human investigation skills.
Prepare SOC workflows with AI
Security foundations rely on people, process, and technology working in balance. This final section brings those elements together, creating your own sketch of a simple SOC integration model, defining review points and safety guardrails, and testing where automated support strengthens analyst-led decisions.
You’ll walk away with a clear, structured view of how to introduce AI responsibly and independently in professional practice.
Syllabus
Week 1
Foundations of AI Agents in Cybersecurity
Lesson 1: Course Introduction
This course introduces AI agents and their transformative role in cybersecurity. You’ll learn how they detect threats, automate response, strengthen SOCs, and address risks, ethics, and governance in AI-driven security.
Lesson 2: Introduction to AI and LLMs in Cybersecurity
Explore how AI and LLMs are revolutionising cybersecurity, moving from traditional tools to advanced agentic systems that detect threats, automate defence, and transform security operations.
Lesson 3: Core Concepts of AI Agents
Understand AI agents’ architecture, autonomy, memory, and learning. Learn how LLMs act as the “brains” behind agents, enabling reasoning, planning, and secure decision-making in real-world cyber defence.
Lesson 4: Datasets and Data Handling for AI Agents in Cybersecurity
Examine types of cybersecurity datasets, learn data preprocessing, and discover augmentation methods that overcome data scarcity, ensuring AI models improve in detecting threats and vulnerabilities.
Week 2
AI Agents in Cybersecurity Operations (Detection & Analysis)
Lesson 5: AI Agents in Threat Detection
Learn how AI agents perform real-time cyber threat detection, automate vulnerability analysis, and classify malware, providing faster, smarter defences against evolving cyberattacks.
Lesson 6: AI Agents in Network and Social Engineering Security
Discover how AI enhances defences against network attacks and phishing threats. Explore intrusion detection systems and how AI generates threat intelligence to anticipate evolving attack strategies.
Lesson 7: Advanced Analysis Capabilities
Explore advanced AI applications like anomaly detection, automated log analysis, reverse engineering, and policy evaluation, equipping analysts with faster, accurate, and scalable cyber defence insights.
Week 3
AI Agents in Cybersecurity Operations (Response & SOC Management)
Lesson 8: AI Agents in Incident Response
Examine how AI automates response workflows, from patch generation to post-attack root cause analysis, ensuring faster recovery and resilience against cybersecurity breaches and attacks.
Lesson 9: Enhancing Security Operations Centres (SOCs) with Agentic AI
Discover how AI transforms SOCs with automation, human-AI co-teaming, compliance monitoring, and adaptive learning, improving efficiency and enabling analysts to focus on critical security tasks.
Week 4
Security, Ethics, and the Future of AI Agents
Lesson 10: Security Risks and Vulnerabilities of AI Agents
Identify vulnerabilities affecting AI agents, including adversarial attacks, prompt injection, and supply chain risks. Learn defensive measures to secure systems against advanced AI threats.
Lesson 11: Ethical Considerations and Governance Frameworks
Explore ethical challenges such as bias, fairness, and accountability. Learn governance strategies and human-in-the-loop systems to ensure AI agents are deployed responsibly in cybersecurity.
Lesson 12: Future Directions and Advanced Concepts
Look ahead to multimodal AI, proactive self-healing systems, and next-generation security strategies. Discover future research opportunities that will shape cybersecurity powered by AI agents.
Lesson 13: Course Conclusion
You have explored the architecture, applications, risks, and governance of AI agents in cybersecurity. You are now equipped to apply, evaluate, and responsibly implement AI-powered defence strategies in real-world environments.
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Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Apply LLMs to automate cybersecurity, using datasets to analyze, learn, and improve threat detection and response over time.
- Evaluate how AI agents detect threats, analyze malware, identify intrusions, and defend against social engineering via real-time analysis and threat intel.
- Design AI-driven cybersecurity workflows for incident response, threat hunting, and SOC optimization with human-AI collaboration and adaptive decisions.
- Identify and mitigate AI security flaws and ethical risks; propose governance for responsible, explainable, and secure use in cybersecurity operations.
Who is the course for?
This course is ideal for security analysts, SOC engineers, incident responders, and learners exploring cyber security careers as well as those seeking practical AI-driven threat detection skills.
Who will you learn with?
Who developed the course?
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