Hands-on tutorials for Claude Code, AI agents, cloud and system design
Awesome LLM Apps is the rare “awesome list” that’s actually a folder full of things you can run. Skip the prompt-snippet sites. This is 100+ working AI agents and RAG apps, each one cloned, customized, and shipped end-to-end under an Apache-2.0 license. View Awesome LLM Apps on GitHub 122,823 stars 18,113 forks Python Apache-2.0 License… Continue reading
500+ AI Agent Projects does what the title promises: it catalogs 500+ agent projects, sorted by both framework (LangGraph, CrewAI, AutoGen, Agno, LlamaIndex) and by industry (Healthcare, Finance, Education, Retail, Cybersecurity, and on). The value isn’t the count, it’s the organization: when you have an idea for an agent, this is the repo where you… Continue reading
public-apis is the open-source phone book for developers, a community-maintained index of around 1,400 free APIs across weather, finance, geocoding, music, sports, machine learning, and everything else you might want to call from a side project. Browse the categories, copy a URL, and you’re sending a real request in under a minute. View public-apis on… Continue reading
Project Based Learning is the practical-tutorials index: curated walkthroughs where you build a full application from scratch in a chosen language, not 30-second “top 10 snippets” listicles. Each entry ends with a real working thing you wrote: a compiler, a web server, a neural network, a small operating system, an e-commerce site. View Project Based… Continue reading
The Algorithms – Python is the largest open-source catalog of algorithms implemented in Python: every classic algorithm from sorting and searching to graph traversal, machine-learning basics, cryptography, and computational geometry, each with a working Python implementation you can read and run. Reference material and study aid in one. View The Algorithms – Python on GitHub… Continue reading
TL;DR 30 sec6 min coredeep dive optional Train an LLM from Scratch is a free MIT repository that walks the entire training pipeline in seven steps, from downloading data and building a transformer piece by piece to aligning the result with DPO and chatting with it, and a free Colab GPU is enough to finish… Continue reading
TL;DR 30 sec6 min coredeep dive optional Machine learning lets software work out its own rules from examples instead of following instructions a programmer typed, and every model in the field trains through one repeating cycle of prediction, penalty, and update. Samuel’s checkers program was already learning at IBM in 1949; a paper he published… Continue reading
Assistants API endpoints stop working on August 26, 2026. If your product still creates threads, polls runs, or attaches tools to assistant objects, this guide moves you to the Responses API and the Conversations API before the deadline, with working Python for every step. Assistants API: What You’ll Learn The Assistants API had four moving… Continue reading
Python SDK 1.0 shipped on August 20, 2026, moving the anthropic package out of its 0.x prefix and into a stable 1.x line. This guide covers every breaking change that can touch real code, reproduces the exact errors you will hit, and walks one project through the complete upgrade from 0.125 to 1.0. Python SDK:… Continue reading