Learning Path184 concepts

Ten sections from first principles to advanced specialisms, curated in the right order so each idea builds on the last.

Your journey

184 concepts · 10 sections

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VII

VIII

Foundational

Start here. These concepts are the prerequisites for everything else.

AI Foundations

The basics before anything else - what AI and machine learning actually are, how neural networks learn, and the building blocks every other concept assumes you know.

10 to explore

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Core

The essential ideas that define modern AI - what most people mean when they say AI.

LLM Architectures

The building blocks inside large language models - how they store knowledge, process text, and generate responses.

27 to explore

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Training & Alignment

How models are built, fine-tuned, and taught to behave the way people actually want them to.

29 to explore

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III

Generative & Multimodal

AI that creates images, audio, and video - and systems that reason across multiple types of input at once.

17 to explore

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Agentic AI

AI that plans, acts, and uses tools autonomously - moving beyond question-and-answer into doing.

18 to explore

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AI Safety & Alignment

The field dedicated to making AI systems behave reliably, honestly, and without causing unintended harm.

17 to explore

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Advanced

Deeper specialisms for engineers, researchers, and the genuinely curious.

MLOps & Infrastructure

The engineering discipline of running AI in production - reliably, efficiently, and at scale.

17 to explore

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VII

Reinforcement Learning & Robotics

AI that learns by doing - and the systems that let it operate in the physical world.

17 to explore

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VIII

Graph Neural Networks

A class of models built for data with relationships - social networks, molecules, maps, and knowledge graphs.

16 to explore

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Specialized Domains

AI applied to medicine, science, audio, and other fields where domain knowledge changes everything.

16 to explore

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