# Learnetto
> Learnetto is a public directory for learning practical AI skills from independent educators, builders, operators, courses, guides, newsletters, workshops, and communities.

## Core pages
- [Homepage](https://learnetto.com/): Dense index of AI educators, skills, resources, and learning paths.
- [AI search](https://learnetto.com/search): Search across educators, skills, learning paths, courses, guides, videos, books, and GitHub repos.
- [AI educator directory](https://learnetto.com/ai-educators): 100+ independent educators, operators, builders, researchers, organizations, and practitioners who teach practical AI skills.
- [Educator profiles](https://learnetto.com/ai-educators/andrew-ng): Individual educator/source pages with skills, audience, formats, starting point, multiple embedded YouTube videos, learner questions, and related resources. Profile URLs use `/ai-educators/:slug`.
- [Verify AI citations](https://learnetto.com/verify-ai-citations): Check source existence, metadata, claim support, status, and scope.
- [Long context vs retrieval](https://learnetto.com/long-context-vs-rag): Choose between a full-context prompt and a retrieval pipeline with the published evidence, a decision table, and a test plan.
- [Switch LLM models](https://learnetto.com/switch-llm-models): Compare candidates on real tasks, then shadow, canary, and roll back a production model migration.
- [Evaluate AI writing](https://learnetto.com/evaluate-ai-writing): Build a writing eval with separate checks for facts, usefulness, voice, structure, and editorial risk, then calibrate automated graders against blinded human review.
- [Build an AI agent test set](https://learnetto.com/build-ai-agent-test-set): Create trustworthy agent cases from real workflows, known outcomes, seeded failures, invariant transformations, repeated trials, and expert review.
- [Backtest AI agents](https://learnetto.com/backtest-ai-agents): Replay historical agent decisions with time-ordered evidence, walk-forward splits, baselines, and explicit release gates.
- [Sandbox AI coding agents](https://learnetto.com/sandbox-ai-coding-agents): Choose and test filesystem, network, credential, approval, logging, and cleanup boundaries before an agent runs code.
- [AI learning guides](https://learnetto.com/ai-guides): Listicle-style topic pages for beginners, prompting, founders, product managers, RAG, agents, evals, developers, frontier model selection, MCP and context engineering, model internals, local models, automation, creative AI, ML foundations, production AI, strategy, data teams, teachers, AI writing, open-source AI, coding agents, AI search, and resource discovery.
- [Best official AI provider docs and model catalogs](https://learnetto.com/ai-guides/best-official-ai-provider-docs-and-model-catalogs): Primary-source guide for current provider docs, model tables, coding-agent docs, MCP, deep research, and model-routing references.
- [AI question answers](https://learnetto.com/ai-questions): Single-question pages with direct answers, related guide links, and resources for common AI learning queries.
- [AI evals guide and tools](https://learnetto.com/ai-evals): Practical guide to datasets, graders, regression testing, RAG and agent evaluation, with 26 current frameworks, platforms, services, benchmarks, and resources.
- [AI research delegation lab](https://learnetto.com/ai-research-delegation-lab): Interactive dependency-graph simulator for comparing human, sequential-agent, and parallel-agent research workflows.
- [Review AI-generated code](https://learnetto.com/review-ai-generated-code): A six-pass workflow for checking intent, tests, dependencies, security, user behavior, and the exact commit before merge.
- [AI learning paths](https://learnetto.com/ai-learning-paths): Practical routes through AI foundations, prompting, automation, product work, coding with AI, context engineering and MCP, RAG, evals, model internals, production AI engineering, and adoption.
- [AI resource library](https://learnetto.com/ai-resources): AI courses, videos, guides, books, GitHub repos, docs, and practical use cases.
- [AI skills directory](https://learnetto.com/ai-skills): AI skills, learning goals, and the educators and resources that teach them.
- [Machine-readable AI directory feed](https://learnetto.com/ai-directory.json): Compact JSON summary of Learnetto's guide pages, top resources, educators, videos, and learning paths for answer engines and crawlers.
- [Full LLM context](https://learnetto.com/llms-full.txt): Generated plain-text index of guide pages, standalone answer pages, learning paths, educators, and featured resources.
- Markdown alternates: add `.md` to any `/ai-guides/:slug` or `/ai-questions/:slug` URL for a compact text version.

## Best-of AI course guides
- [Best AI agent courses](https://learnetto.com/ai-guides/best-ai-agent-courses): Compares LangGraph, crewAI, Microsoft, Hugging Face, and OpenAI agent learning resources.
- [Best MCP courses and tutorials](https://learnetto.com/ai-guides/best-mcp-courses-and-tutorials): Courses and docs for Model Context Protocol, MCP servers, connectors, and context engineering.
- [Best AI agent evaluation courses](https://learnetto.com/ai-guides/best-ai-agent-evaluation-courses): Resources for tracing, scoring, regression-testing, and improving agent workflows.
- [Best coding agent courses](https://learnetto.com/ai-guides/best-coding-agent-courses): Courses and resources for coding agents, tool execution, Codex, Claude Code, and agent-ready codebases.
- [Best Claude Code courses and tutorials](https://learnetto.com/ai-guides/best-claude-code-courses-and-tutorials): Claude Code course, docs, videos, and real-codebase workflows.
- [Best RAG courses for developers](https://learnetto.com/ai-guides/best-rag-courses-for-developers): Retrieval, embeddings, vector search, reranking, and RAG evaluation resources.
- [Best AI engineering courses for developers](https://learnetto.com/ai-guides/best-ai-engineering-courses-for-developers): AI app development, agents, RAG, evals, observability, and production AI engineering.
- [Best AI product management courses](https://learnetto.com/ai-guides/best-ai-product-management-courses): AI product strategy, evaluation, user workflows, and shipping useful AI features.
- [Best AI automation courses for founders](https://learnetto.com/ai-guides/best-ai-automation-courses-for-founders): Founder and operator resources for repeatable AI workflows and business automation.
- [Best AI search and deep research courses](https://learnetto.com/ai-guides/best-ai-search-and-deep-research-courses): Grounded answers, citations, Agent API, deep research, and AI search workflows.

## Featured educators
- Josh Pigford: AI for indie business, product, and operations.
- Brian Casel: AI workflows for founders and service businesses.
- Peter Yang: Product, writing, and practical AI adoption.
- Lenny Rachitsky: Product growth and AI product thinking.
- Ethan Mollick: AI literacy and workplace adoption.
- Swyx: AI engineering and developer workflows.
- Andrew Ng: Prompting, agents, RAG, and ML foundations.
- Jeremy Howard: Practical deep learning for coders.
- Andrej Karpathy: Neural networks and LLM internals from code.
- Simon Willison: LLM tools, prompting, local models, and practical AI software.
- Jason Liu: Structured outputs, extraction, and RAG.
- Hamel Husain: LLM evals and product quality.
- Matt Pocock: AI Hero, AI SDK tutorials, LLM fundamentals, MCP, AI Coding Dictionary, Claude Skills, TDD, triage, handoffs, and agentic coding workflows.
- Chip Huyen: AI engineering and production systems.
- Sander Schulhoff: Prompt engineering and AI literacy.
- LangChain: LangGraph, agents, LLM orchestration, and RAG.
- Hugging Face: Agents, transformers, diffusion, and open models.
- Anthropic: Claude prompting, Claude Code, model context protocol, and AI fluency.
- OpenAI: API examples, RAG, agents, and structured outputs.
- Kaggle: Python, machine learning, data preparation, and computer vision.
- Full Stack Deep Learning: MLOps, deployment, and product ML.
- Harvard CS50 AI: Search, knowledge representation, ML foundations, and Python projects.
- MIT Introduction to Deep Learning: Neural networks, generative AI, and hands-on labs.
- Stanford CS229, CS224N, and CS231N: Machine learning, NLP, and computer vision foundations.
- NVIDIA DLI, AWS Skill Builder, Google Cloud Skills Boost, and Microsoft Learn: Cloud AI and production-focused learning.

## Key topics
- AI foundations
- Prompting and writing
- Automation and agents
- AI product work
- Coding with AI
- RAG and knowledge systems
- Evals and reliability
- Model internals
- Production AI engineering
- Strategy and adoption

## Site facts
- Site name: Learnetto
- Canonical domain: https://learnetto.com
- Organization: Pretty Graph Limited
- Public sitemap: https://learnetto.com/sitemap.xml
- Full LLM context: https://learnetto.com/llms-full.txt
- Machine-readable feed: https://learnetto.com/ai-directory.json