AI Fundamentals: From Understanding to Implementation

A Comprehensive Course for Technical Professionals

AI is transforming how we build and deploy software – but with that transformation comes a new attack surface. This hands-on course equips technical professionals with the knowledge to understand AI systems, recognize their vulnerabilities, and defend them in production. From foundational concepts through real-world attacks to layered defense architectures, you’ll build the fluency needed to work with AI securely and effectively.

Who Is This For?

This course is designed for:

  • Security professionals assessing and mitigating AI-specific risks
  • Developers building AI-powered applications and integrations
  • Architects designing secure AI system deployments
  • DevOps and platform engineers deploying and managing AI workloads
  • Technical managers overseeing AI initiatives and security posture
  • Anyone with a technical background wanting to understand AI security from the ground up

What You’ll Learn

Chapter 1: Introduction to AI and LLMs

  • Core AI concepts: from rule-based systems to LLMs and the Transformer architecture
  • Key providers and models: OpenAI, Anthropic, Google, Meta, DeepSeek, and more
  • Hands-on prompt engineering and inference techniques with real APIs
  • Agentic AI: understanding autonomous AI systems and their trust boundaries

Chapter 2: Vulnerabilities and Attacks on LLMs

  • The complete AI attack surface mapped to OWASP LLM Top 10 (2025)
  • Prompt injection, data poisoning, model theft, and output exploitation
  • Agentic attack vectors mapped to OWASP Agentic AI Top 10 (2026)
  • Named case studies: real companies, real incidents, real lessons

Chapter 3: Protecting LLMs from Attacks

  • The Security for AI Blueprint: a 6-layer defense framework
  • OWASP-to-Blueprint mapping: every attack category matched to defense controls
  • Trend Vision One, AI Scanner, AI Guard, and the LEARN Architecture
  • Building an AI security culture: red-teaming, incident response, compliance
Prerequisites

While no prior AI experience is required, it is recommended (but not mandatory) that you have:

  • Basic understanding of APIs and system architecture
  • Familiarity with software development processes

As recommended reading to understand AI systems better, we suggest:

Technical Requirements

To participate in this course and follow the hands-on exercises, you’ll need:

  • A computer with internet access
  • A modern web browser
  • An n8n instance (free cloud trial or local installation) for hands-on labs
  • An OpenAI API key (or compatible LLM API key) for lab exercises
  • Administrative rights for local n8n installation (optional)

What You’ll Gain

By the end of this course, you will be able to:

  • Understand the complete AI technology stack from neural networks through agentic systems
  • Map the AI attack surface using OWASP LLM Top 10 and Agentic AI Top 10 frameworks
  • Explain and demonstrate real-world AI attack techniques to stakeholders and leadership
  • Design layered security architectures using the Security for AI Blueprint
  • Select and configure defense controls that map to specific threat categories
  • Build organizational practices for AI red-teaming, incident response, and compliance

Ready to build your AI foundation?

Start with Chapter 1