The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
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Learn AI Engineering! Learn it. Build it. Ship it for others.
Translated100-Days-Of-ML-Code Chinese version
- machine-learning
- python
- 100-days-of-ml-code
- chinese-simplified
AWS zero to hero repo for devops engineers to learn AWS in 30 Days. This repo includes projects, presentations, interview questions and real time examples.
"Context engineering is the delicate art and science of filling the context window with just the right information for the next step." — Andrej Karpathy. A frontier, first-principles handbook inspired by Karpathy and 3Blue1Brown for moving beyond prompt engineering to the wider discipline of context design, orchestration, and optimization.
A multi-module course teaching everything you need to know about using GitHub Copilot as an AI Peer Programming resource.
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learn LLM inference system on Apple Silicon for systems engineers: build a tiny vLLM + Qwen
- course
- large-language-model
- llm
- python
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Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
Follow along with my AI Agents Masterclass videos! All of the code I create and use in this series on YouTube will be here for you to use and even build on top of!
Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning
- cli
- deep-learning
- education
- from-scratch
Course materials for Zurich Initiative for Computational Economics (ZICE) 2014
A structured, multi-agent Claude Code learning environment for mastering Retrieval-Augmented Generation (RAG)