NirDiamant/GenAI_Agents
This repository offers a comprehensive collection of over 50 tutorials and implementations for Generative AI Agent techniques, ranging from basic conversational bots to complex multi-agent systems,...
Awesome MCP › MCP Resources & Educational Materials
patchy631/ai-engineering-hub
The AI Engineering Hub is a comprehensive repository designed to provide in-depth tutorials and practical resources focused on Large Language Models (LLMs), Retrieval-Augmented Generation (RAGs), and real-world applications of AI agents. This project aims to support a wide range of users, from beginners to experienced practitioners and researchers, by offering detailed guides and examples that facilitate understanding and hands-on experimentation in AI engineering. The repository emphasizes the importance of staying current with rapid advancements in AI technology by combining theoretical knowledge with practical implementation strategies. Key features of the AI Engineering Hub include extensive tutorials that cover foundational and advanced topics related to LLMs and RAGs, which are critical components in modern AI systems for natural language understanding and generation. Additionally, the repository showcases real-world AI agent applications, providing users with concrete examples to implement, adapt, and scale in their own projects. This practical approach helps bridge the gap between academic research and industry applications. The project also encourages community involvement by inviting contributions to expand and improve the content, fostering a collaborative environment for AI enthusiasts and professionals. Subscribers to the associated newsletter gain access to additional resources, such as a free Data Science eBook containing over 150 essential lessons, which further supports continuous learning and skill development. Licensed under the MIT License, the AI Engineering Hub is openly accessible and designed to be a valuable resource for anyone interested in advancing their knowledge and capabilities in AI engineering. The repository's structure and content make it an ideal starting point for those looking to deepen their expertise in LLMs, RAGs, and AI agent technologies, while also providing practical tools and examples for real-world application.
https://github.com/patchy631/ai-engineering-hub
Also in MCP Resources & Educational Materials
NirDiamant/agents-towards-production
This repository offers end-to-end, code-first tutorials for building and deploying production-grade Generative AI agents, scaling from prototype to enterprise.
microsoft/mcp-for-beginners
An open-source curriculum designed to teach the concepts and fundamentals of the Model Context Protocol (MCP) with practical coding examples in multiple programming languages.
Arindam200/awesome-ai-apps
A comprehensive collection of practical examples, tutorials, and tools for building powerful LLM-powered AI applications, including chatbots, agents, and workflows, with a focus on the Model Context Protocol (MCP).
modelcontextprotocol/modelcontextprotocol
The Model Context Protocol project provides a standardized specification and schema for managing model context to enable interoperability in model-driven systems.
heilcheng/awesome-agent-skills
A curated repository of modular skills, tools, and tutorials for enhancing AI coding agents like Claude, Codex, Copilot, and VS Code through dynamic instruction files.
ashishps1/learn-ai-engineering
A comprehensive curated collection of free resources to learn AI, Machine Learning, Large Language Models, AI Agents, and the Model Context Protocol from scratch.
zebbern/claude-code-guide
A comprehensive and detailed guide for Claude Code CLI tool, covering all commands, installation, configuration, and Model Context Protocol (MCP) integration for optimized use.