Agentic AI for Cybersecurity (Video Course)

Description

Unlock the power of Agentic AI by learning how to build, orchestrate, and secure intelligent AI agents that can collaborate to automate cybersecurity operations, accelerate threat response, and enhance defensive capabilities.

Cybersecurity is rapidly evolving beyond traditional automation. In Agentic AI for Cybersecurity, you'll learn how to design and manage teams of AI agents capable of reasoning, communicating, and taking action to solve complex security challenges.

Starting with the foundations of Agentic AI, you'll explore modern concepts such as Retrieval-Augmented Generation (RAG), Agentic RAG, Model Context Protocol (MCP), and Agent2Agent (A2A) communications. You'll then dive into leading orchestration frameworks including LangChain, LangGraph, CrewAI, n8n, Apache Airflow, and LlamaIndex to build scalable AI systems and agentic harnesses for cybersecurity operations and beyond.

Through practical examples, you'll learn how AI agents can support threat intelligence, SOC operations, incident response, penetration testing, and security automation. You'll also explore the risks associated with autonomous AI systems and learn how to secure, govern, and monitor agentic environments.

By the end of this course, you'll have the skills needed to architect and deploy multi-agent cybersecurity solutions that help organizations operate faster, smarter, and more proactively.

Skill Level:

Intermediate to advanced

Learn How To:

• Build and orchestrate multi-agent AI systems for cybersecurity operations
• Use LangChain, LangGraph, CrewAI, n8n, Apache Airflow, and LlamaIndex to create agent workflows
• Implement RAG, Agentic RAG, MCP, and A2A architectures
• Develop AI-powered agents for threat intelligence, SOC automation, and incident response
• Automate reconnaissance, vulnerability analysis, and penetration testing workflows
• Secure agentic systems against emerging AI-related threats and risks

Course Requirement:

Students should have a working knowledge of cybersecurity concepts and basic familiarity with scripting or automation. Experience with Python is helpful but not required.

Who Should Take This Course:

This course is designed for security analysts, security engineers, SOC personnel, penetration testers, DevSecOps practitioners, security architects, automation engineers, and technology leaders who want to leverage AI to improve cybersecurity operations. It is ideal for professionals seeking practical skills in building, orchestrating, and securing the next generation of AI-powered security systems.

Course Outline:

Lesson 1: Foundations of Agentic AI Systems

Build a strong foundation in Agentic AI by learning what AI agents are, how they differ from traditional automation, and how they operate through reasoning loops such as ReAct and Plan-and-Execute. You'll explore the major categories of AI agents and discover real-world cybersecurity use cases, while also becoming familiar with the tools, resources, and repositories used throughout the course.

Lesson 2: Retrieval-Augmented Generation (RAG), Agentic RAG, and Model Context Protocol (MCP)

Learn how modern AI systems access and leverage external knowledge using RAG and Agentic RAG architectures. Explore vector databases, embeddings, and model context management while gaining hands-on exposure to open-weight AI models, Hugging Face, Ollama, AnythingLLM, vLLM, ComfyUI, and WebMCP. This lesson establishes the building blocks for creating intelligent, context-aware cybersecurity agents.

Lesson 3: Enabling Interoperability: Protocols for the Internet of Agents

Discover how AI agents communicate and collaborate across distributed environments. You'll explore the Agent2Agent (A2A) protocol, compare emerging interoperability standards such as AGNTCY and ACP, and learn how secure agent discovery works through Agent Name Services (ANS). The lesson concludes with an examination of the cybersecurity risks and security controls associated with inter-agent communication.

Lesson 4: Orchestration with LangChain, LangGraph, and LlamaIndex

Learn how to build robust AI applications and orchestrate intelligent workflows using leading agent frameworks. You'll develop AI-powered applications with LangChain, evaluate them using LangSmith, build agent-driven workflows with LangGraph, and leverage LlamaIndex for knowledge integration. You'll also learn how to create MCP-enabled services using FastMCP for secure tool and data access.

Lesson 5: Exploring CrewAI, n8n, Apache Airflow, and Other Agentic Frameworks

Expand your agentic toolkit with additional frameworks designed for collaboration, workflow automation, and operational scale. Learn how CrewAI enables coordinated agent teams, how n8n simplifies agent orchestration through low-code interfaces, and how Apache Airflow supports complex, data-driven workflows. You'll gain insight into selecting the right framework based on your cybersecurity use case.

Lesson 6: The Architect's Cockpit: AI-Powered IDEs and Coding Agents

Explore the next generation of AI-assisted software development environments. You'll learn how tools such as Cursor, Windsurf, OpenAI Codex, Claude Code, Warp, and other coding agents can accelerate development, automate tasks, and improve productivity. You'll also examine agent memories, skills, workflows, and secure code review techniques to help build safer AI-enabled applications.

Course Summary

Review the key technologies, frameworks, architectures, and best practices covered throughout the course. You'll leave with a practical roadmap for designing, deploying, orchestrating, and securing agentic AI systems that can enhance modern cybersecurity operations.

Sample Content

Table of Contents

Lesson 1: Foundations of Agentic AI Systems

Lesson 2: Retrieval-Augmented Generation (RAG), Agentic RAG, and Model Context Protocol (MCP)

Lesson 3: Enabling Interoperability: Protocols for the Internet of Agents

Lesson 4: Orchestration with LangChain, LangGraph, and LlamaIndex

Lesson 5: Exploring CrewAI, n8n, Apache Airflow, and Other Agentic Frameworks

Lesson 6: The Architect's Cockpit: AI-Powered IDEs and Coding Agents

Course Summary

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