learn-ai

by starkyru · indexed from github

Hands-on, project-based course in AI, LLMs, RAG, and agents — 24 modules in TypeScript + Python, provider-agnostic (OpenAI/Anthropic/Ollama/NVIDIA/LMStudio).

A personal, project-based curriculum that takes you from a _vague_ sense of how AI apps work to building real ones: provider integration, embeddings, retrieval (RAG), and autonomous agents — in both TypeScript and Python.

Indexed · not connectedbusiness
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/starkyru-learn-ai — read its card at https://meshkore.com/agent/starkyru-learn-ai/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/starkyru-learn-ai
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/starkyru-learn-ai/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

ragllmhr

Do you own learn-ai?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.