# Fanout

> Fanout maps serious technical learning across AI research, system design, machine learning mathematics, inference engineering, open robotics, practical labs, and daily papers.

Fanout is an independent educational product by Suraj Gaud. Public pages, previews, tools, and Daily paper notes may be summarized and cited. Pro lessons and account-specific pages are access-controlled and are intentionally absent from these files.

## Start here

- [Fanout](https://fanout.sh/): Product map, current learning note, course directory, and the main public discovery surface.
- [Learning roadmaps](https://fanout.sh/roadmap): Visual roadmaps for AI research, system design, and ML mathematics.
- [Pricing](https://fanout.sh/pricing): Current Free, Single Track, and Complete access options.

## Courses

- [AI Research](https://fanout.sh/ai): A sequenced path from mathematical foundations through modern language models, alignment, and research practice.
- [System Design In Depth](https://fanout.sh/system): System design notes, case studies, curriculum, and from-scratch implementation previews.
- [Machine Learning Mathematics](https://fanout.sh/ml-math): A 12-module mathematics path spanning sets, linear algebra, calculus, probability, and inference.
- [Inference Engineering](https://fanout.sh/inference-eng): The public roadmap for the upcoming production LLM inference course.
- [Inference course comparison](https://fanout.sh/inference-eng/courses): A disclosed, evidence-based comparison of current LLM inference courses and open resources.
- [Open Robotics](https://fanout.sh/open-robotics): The public curriculum preview for the upcoming open-stack robotics course.

## Free tools and ongoing learning

- [Fanout Labs](https://fanout.sh/labs): Explore 15 curated interactive Labs for AI, inference, system design, evaluation, research, and everyday technical work.
- [Daily papers](https://fanout.sh/daily): A dated calendar of foundational and current technical papers with concise reading notes.
- [Fanout blog](https://fanout.sh/blog): Practical field notes across AI research, systems, inference, and ML mathematics.
- [Knowledge Topography](https://fanout.sh/knowledge-graph): A navigable map connecting concepts across the three active learning tracks.
- [Technical tools](https://fanout.sh/tools): A curated directory of useful AI, ML, and system design tools.
- [Study With Me](https://fanout.sh/study-with-me): Public guided study sessions and previews of people learning in public.

## Reference collections

- [AI glossary](https://fanout.sh/ai/glossary): Plain-English definitions for AI and machine learning terms.
- [Foundational AI papers](https://fanout.sh/ai/papers): A curated reading sequence of papers that shaped modern AI.
- [AI researcher resources](https://fanout.sh/ai/resources): Courses, books, lectures, and repositories organized by topic and level.
- [System design resources](https://fanout.sh/system/resources): Books, engineering blogs, tools, and channels for architecture study.

## Optional

- [Full Fanout context](https://fanout.sh/llms-full.txt): Expanded descriptions of canonical public routes and Daily papers.
- [XML sitemap](https://fanout.sh/sitemap.xml): Canonical indexable URLs and honest content modification dates where known.
- [Daily paper RSS feed](https://fanout.sh/feed.xml): Machine-readable updates for the Daily paper archive.
- [Blog RSS feed](https://fanout.sh/blog/feed.xml): Machine-readable updates for Fanout field notes.