Awesome AI Agents › Educational & Learning Agents
AI Engineering from Scratch provides an in-depth, practical curriculum designed to equip individuals with the skills to build AI systems from foundational mathematical concepts to advanced autonomous agents. Unlike typical AI learning resources that offer fragmented information, this project presents a cohesive, linear learning path across 20 phases and 503 lessons, emphasizing end-to-end understanding. Learners will build every algorithm from first principles, including backpropagation, tokenizers, attention mechanisms, and agent loops, before integrating with production libraries like PyTorch. The curriculum spans multiple programming languages including Python, TypeScript, Rust, and Julia, ensuring a broad skill set. Each lesson focuses on deriving the math, writing the code, running tests, and producing a reusable artifact. The project explicitly avoids hand-holding and encourages a deep understanding of underlying mechanisms rather than mere API calls. It also includes integrated agent skills for personalized learning paths and progress checking, making it an excellent resource for aspiring AI engineers who seek a rigorous, hands-on approach to AI development.
https://github.com/rohitg00/ai-engineering-from-scratch
AI Agents for Beginners is a Microsoft educational course with 10 lessons teaching the fundamentals and practical skills to build AI agents using Azure AI and GitHub models, supported by multi-language resources and community engagement.
A comprehensive collection of free resources to learn AI, machine learning, large language models, and AI agents from scratch.
A comprehensive educational repository providing clear, step-by-step Python implementations and explanations of a wide range of reinforcement learning algorithms for interactive learning and deep understanding.
TheoremExplainAgent is an AI system that generates long-form Manim videos to visually explain mathematical theorems, enhancing understanding through multimodal explanations combining text, visuals, and audio.
Inno Agent is a personal learning agent with three explicit memory layers, a cron scheduler, Feishu and WeChat channels and a workspace-scoped practice terminal, built on the Pi coding-agent SDK.
LangChain-OpenTutorial is an open, community-driven tutorial resource providing comprehensive learning materials and practical examples for LangChain and LangGraph technologies, suitable for users of all skill levels worldwide.
Groundhog is an AI coding assistant designed as a teaching tool to help users understand and leverage the inner workings of coding agents like Cursor through detailed code explanations and a modern Rust-based CLI.
An educational repository with code and notebooks accompanying the "Quick Start Guide to Large Language Models - Second Edition" book, covering practical applications and advanced techniques for large language models.