# AI and Machine Learning Fundamentals

> Master the core concepts of AI and ML. Understand model architectures, training pipelines, and the foundational mechanics required for AI security.

Canonical: https://codelivly.com/learning-paths/ai-and-machine-learning-fundamentals
Last updated: 2026-09-28

| | |
|---|---|
| Level | Beginner |
| Category | Cybersecurity |
| Rooms | 5 |
| Lessons | 19 |
| Estimated time | 2 h 30 min |

This beginner-friendly learning path builds the essential foundation for cybersecurity professionals looking to specialize in AI red teaming and adversarial machine learning. You will explore the core concepts of artificial intelligence, machine learning, and deep learning without needing a heavy math background. The curriculum covers how models are trained, the anatomy of neural networks and transformers, the end-to-end ML lifecycle (data collection, training, deployment, inference), and the fundamental architectural weaknesses that emerge at each stage. By the end of this path, you will speak the language of data scientists and be ready to identify where AI systems are most vulnerable to attack.

## Rooms in this path

1. [How Machine Learning Works](https://codelivly.com/rooms/how-machine-learning-works) - Master the core mechanics of machine learning, from data ingestion to model deployment, and understand where security…
2. [Neural Networks and Deep Learning Basics](https://codelivly.com/rooms/neural-networks-and-deep-learning-basics) - Master the building blocks of modern AI. Understand perceptrons, hidden layers, activation functions, and…
3. [How Large Language Models Work](https://codelivly.com/rooms/how-large-language-models-work) - Decode the technology behind modern AI. Learn tokenization, embeddings, and the self-attention mechanism that powers…
4. [Transformers and Attention Explained Simply](https://codelivly.com/rooms/transformers-and-attention-explained-simply) - Demystify the Transformer architecture. Understand self-attention, Query-Key-Value mechanics, and why this…
5. [Training Data, Fine-Tuning and RLHF Explained](https://codelivly.com/rooms/training-data-fine-tuning-and-rlhf-explained) - Understand how LLMs learn. Explore pre-training, fine-tuning, and Reinforcement Learning from Human Feedback (RLHF) and…

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- [Career path: AI Red Teaming and Adversarial ML](https://codelivly.com/career-paths/ai-red-teaming-and-adversarial-ml)
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