Oreilly – Agentic AI for Cybersecurity 2026-8

Oreilly – Agentic AI for Cybersecurity 2026-8

10 Sep at 12:51 pm

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Description

Agentic AI for Cybersecurity Course. This course explores how to build, manage, and secure intelligent AI agents to automate cybersecurity operations and accelerate threat response. Cybersecurity is rapidly moving beyond traditional automation, and leveraging new technologies is essential. This comprehensive course teaches you how to design and manage teams of AI agents that can reason, communicate, and act to solve complex security challenges. Learners begin with the fundamentals of Agentic AI and delve into modern constructs such as Retrieval-Driven Generation (RAG), Agentic Guided Generation (Agentic RAG), Model Context Protocol (MCP), and Agent-to-Agent (A2A) communications. During this course, you will learn about key management and orchestration frameworks, including LangChain, LangGraph, CrewAI, n8n, Apache Airflow, and LlamaIndex, to implement scalable AI systems for cybersecurity operations. Through practical examples, you will learn how AI agents can support threat analysis, security operations center (SOC), incident response, penetration testing, and security automation processes. You will also learn about the risks associated with AI-powered systems and how to secure, govern, and monitor agent environments. This course will help you design multi-agent security solutions and lead organizations to become smarter and more proactive against threats. It will also explain how reasoning loops like ReAct and Plan-and-Execute work, and introduce tools like Hugging Face, Ollama, vLLM, and FastMCP to manage AI models. Examining inter-agent communications, intelligent agent registration, and methods for securing developed code with tools such as Cursor and Claude Code are other main topics of this comprehensive training.

What you will learn

Building and orchestrating multi-agent systems: Creating and managing AI teams to automate cybersecurity operations.
Use advanced frameworks: Leverage LangChain, LangGraph, CrewAI, n8n, Apache Airflow, and LlamaIndex to build workflows.
Implementing new architectures: Implementing RAG, Agentic RAG, MCP, and A2A structures in real projects.
Security Agent Development: Building intelligent agents for Security Operations Center (SOC), incident response, and threat analysis.
Penetration testing automation: Automating the processes of identification, vulnerability analysis, and penetration testing in the network.
Securing operating systems: Protecting AI systems against emerging threats and managing their risks.

This course is suitable for people who:

Cybersecurity analysts and engineers: professionals who aim to enhance security operations with artificial intelligence.
Prestel Security Operations Center (SOC): People looking to automate incident analysis and response.
Penetration testers and DevSecOps engineers: professionals who want to automate security assessment processes.
Security architects and automation engineers: People who seek to design advanced and intelligent security solutions.
Technology leaders: Managers who plan to use AI capabilities to improve their organization’s cyber defenses.