awesome-artificial-intelligence

This repository is a curated collection of resources for people learning about or working in artificial intelligence. It covers books, online courses, landmark research papers, newsletters, frameworks, and tools, organized into sections by topic and skill level.

The collection focuses on what the maintainer calls AI engineering: the practical work of building production AI systems, including retrieval-augmented generation (a technique for giving AI models access to private documents), agent frameworks, evaluation methods, and deployment. Alongside those applied topics, it also links to foundational academic material for people who want deeper theoretical grounding.

The books section includes both modern practical titles covering machine learning pipelines, generative models, and end-to-end AI product building, as well as classic foundational texts on neural networks, reinforcement learning, and general AI theory. The courses section is split by difficulty level, with beginner options from Google and Hugging Face and more advanced material from Stanford and MIT. A separate papers section lists the key research that shaped the architectures and techniques in widespread use today.

The tools section covers currently active AI models, coding assistants, image and video generation services, and audio tools. Each entry includes a one-line note on what the tool is best suited for, making it useful as a quick orientation map rather than a deep technical guide.

The repository contains no code of its own. It is a living reference document that the maintainer updates over time. Its focus has shifted toward practical AI system building, and it now functions primarily as a starting-point index for engineers building AI products rather than a survey of academic research.