AI Security Masterclass: Secure LLMs & AI Agents

About this course

This course contains the use of artificial intelligence AI Security Masterclass: Secure LLMs & AI Agents

Learn how to secure modern AI applications by building and understanding the same production-grade defenses used to protect real LLM-powered systems.

This course is designed for software engineers, security engineers, DevSecOps practitioners, AI developers, and anyone who wants practical, code-first experience securing Large Language Models (LLMs), AI agents, and AI gateways.

Unlike theory-heavy AI security courses, every technical section is built around real production source code. You'll read it, run it, break it, test it, and understand why each security control exists.

What You'll Learn

Understand how AI security differs from traditional application security

Learn the foundations of machine learning, transformers, embeddings, tokens, and LLMsIdentify the unique attack surface of AI applications

Build production-grade security controls for LLM applications

Detect and block prompt injection attacks

Implement API rate limiting and abuse protection

Detect secrets such as API keys, JWTs, GitHub tokens, and AWS credentials

Automatically redact personally identifiable information (PII)Defend against Unicode, encoding, and prompt evasion techniques

Protect AI applications from token exhaustion and denial-of-service attacks

Build secure audit logging without leaking sensitive data

Scan dependencies and reduce AI supply-chain risk

Add guardrails to autonomous AI agents and tool execution

Combine multiple defenses into a complete AI gateway pipeline

Test every security layer using a real production test suite

Course Structure

The course contains 15 compreh

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