Free AI Resources That Are Actually Worth Your Time
A curated path into AI from the ground up — no paywalls, no hype, just the sources our team reads.
There is an ocean of AI content and most of it is recycled. This collection is the short list we actually read: the primary sources first, then the few secondary resources that add real understanding instead of noise.
- 1Karpathy’s Neural Networks: Zero to Hero
Andrej Karpathy builds neural networks from scratch in a video series that removes the black-box magic. The single best free starting point for understanding how models actually compute.
- 2The Illustrated Transformer
Jay Alammar’s visual walkthrough of the transformer architecture. Still the clearest explanation of attention mechanisms, years after publication.
- 3Hugging Face Learn
Free interactive courses on transformers, NLP and agents with hands-on notebooks. The practical companion to the theory, backed by the ecosystem’s main hub.
- 4fast.ai Practical Deep Learning
The "top-down" alternative to Karpathy: build real models first, learn theory as needed. Free course materials with a pragmatic, code-first philosophy.
- 5OpenAI Documentation
The de-facto reference for the ChatGPT API ecosystem, including function calling, structured outputs and prompting patterns that are now industry vocabulary.
- 6Anthropic Documentation
Claude’s docs with genuinely useful engineering guidance — prompt caching, tool use and the "build effective agents" essays are worth reading regardless of which model you use.
- 7arXiv
The preprint server where AI research actually lands. Rough, fast and unfiltered — the closest thing to reading the field’s pulse before it reaches the blogs.
- 8Google AI
Primary source for Gemini and Google’s research, including the original Transformer paper and later system cards that describe real-world model behavior.
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