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AI Security
Understand how modern AI actually works, then attack it: prompt injection, guardrail bypasses, RAG poisoning, agent and tool abuse, and the supply chain behind the models.
26 exercises
2 chapters
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Chapter 1
AI Fundamentals
How modern AI actually works: data and models, neural networks, embeddings, transformers and large language models, and how applications are built on top of them. The groundwork before you attack any of it.
AI Fundamentals: Introduction
Pro
AI Fundamentals: Data, Features & Labels
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AI Fundamentals: Types of Machine Learning
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AI Fundamentals: How Models Learn
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AI Fundamentals: Overfitting & Generalization
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AI Fundamentals: Evaluating Models
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AI Fundamentals: Classic ML Algorithms
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AI Fundamentals: Neural Networks
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AI Fundamentals: Deep Learning
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AI Fundamentals: Embeddings & Vectors
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AI Fundamentals: Tokenization
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AI Fundamentals: Transformers & Attention
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AI Fundamentals: Large Language Models
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AI Fundamentals: Training an LLM
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AI Fundamentals: Inference & Sampling
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AI Fundamentals: Prompting
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AI Fundamentals: Limitations & Hallucinations
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AI Fundamentals: Retrieval-Augmented Generation
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AI Fundamentals: Tool Use & Agents
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AI Fundamentals: Multimodal Models
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AI Fundamentals: Using Models in Practice
Pro
Chapter 2
AI Security
Find and exploit weaknesses in LLM and ML applications: direct and indirect prompt injection, guardrail and filter evasion, RAG poisoning, agent and tool abuse reaching real sinks, and model supply-chain attacks.
Recommended: Complete Chapter 1 first