AI智能体学习资源有哪些？2026年最新精选课程与框架教程

Introduction

This guide presents a meticulously curated collection of resources for studying, building, and evaluating autonomous AI and Large Language Model (LLM) agents. It is designed for developers, researchers, and technical leaders seeking to navigate the rapidly evolving landscape of agentic AI. The resources are categorized for structured learning, from foundational concepts to practical implementation and rigorous evaluation.

本指南精心整理了一系列用于学习、构建和评估自主人工智能（AI）及大语言模型（LLM）智能体的资源。它专为希望探索快速发展的智能体AI领域的开发者、研究人员和技术领导者设计。资源按结构化学习路径分类，涵盖从基础概念到实践实现，再到严格评估的完整流程。

Foundational Courses

This section lists comprehensive educational programs that provide a solid theoretical and practical grounding in AI agents.

本节列出了全面的教育课程，为学习AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.提供坚实的理论和实践基础。

• Advanced Large Language Model Agents — A graduate-level course exploring the design and deployment of LLM-powered agents. Covers LLM foundations, reasoning, tool use, multi-agent collaboration, and applications. Features guest lectures from leading researchers.

  高级大语言模型智能体 — 一门研究生级别的课程，探讨基于LLM的智能体的设计与部署。涵盖LLM基础、推理、工具使用、多智能体协作及应用。包含顶尖研究人员的客座讲座。

• Agentic AI and AI Agents: A Primer for Leaders — A concise course for non-technical executives and product managers. Provides relevant theory and teaches no-code approaches to implementing AI agents using custom GPTs.

  智能体AI与AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.：领导者入门 — 为非技术高管和产品经理设计的简明课程。提供相关理论，并教授使用自定义GPT实现AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.的无代码方法。

• AI Agents Masterclass — A beginner-friendly episodic series with full code walkthroughs to build AI agents. Covers LangChain, LangGraph, RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses. techniques, and n8n workflow agents.

  AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.大师班 — 一个适合初学者的系列课程，提供完整的代码演练来构建AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.。涵盖LangChain、LangGraph、RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses.技术和n8n工作流智能体。

• Hugging Face's AI Agents Course — A hands-on program guiding from foundational concepts to deploying autonomous agents. Covers implementation using frameworks like smolagents, LlamaIndex, and LangGraph, including assignments and a final project.

  Hugging Face的AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.课程 — 一个实践性项目，指导学员从基础概念到部署自主智能体能够理解复杂输入、进行推理和规划、可靠使用工具并从错误中恢复的LLM系统，在明确任务后独立规划和操作，可根据环境反馈调整行为。。涵盖使用smolagents、LlamaIndex和LangGraph等框架的实现，包括作业和最终项目。

• Learn AI Agents Handbook — An interactive handbook/roadmap for building autonomous AI agents.

  学习AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.手册 — 一份用于构建自主AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.的交互式手册/路线图。

• Microsoft's AI Agents for Beginners — A comprehensive open-source course comprising 11 lessons. Covers tool integration, RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses., agentic design patterns, multi-agent systems, and deployment, focused on Microsoft frameworks.

  微软的AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.入门 — 一个包含11节课的综合性开源课程。涵盖工具集成、RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses.、智能体设计模式、多智能体系统由多个相互协作的AI智能体组成的系统，能够处理复杂任务并通过智能体间的通信和协调实现更高级的自动化功能。和部署，侧重于微软框架。

• Multi AI Agent Systems with crewAI — A beginner-friendly course teaching how to build and deploy AI agents using the CrewAI framework. Covers tools management, memory, error handling, and agent cooperation.

  使用crewAI构建多AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.系统 — 一门适合初学者的课程，教授如何使用CrewAI框架构建和部署AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.。涵盖工具管理、记忆、错误处理和智能体协作。

Conceptual Guides

These in-depth articles, surveys, and playbooks offer strategic insights and architectural understanding of AI agents.

这些深入的文章、综述和操作手册提供了关于AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.的战略见解和架构理解。

• A Practical Guide to Building Agents (OpenAI) — A step-by-step playbook offering best practices for designing autonomous AI agents, covering problem identification, architecture, and success measurement.

  构建智能体实用指南（OpenAI） — 一份循序渐进的操作手册，提供设计自主AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.的最佳实践，涵盖问题识别、架构设计和成功度量。

• A Survey on Large Language Model based Autonomous Agents — An academic survey that systematically examines the construction, applications, and evaluation of LLM-based autonomous agents.

  基于大语言模型的自主智能体能够理解复杂输入、进行推理和规划、可靠使用工具并从错误中恢复的LLM系统，在明确任务后独立规划和操作，可根据环境反馈调整行为。综述 — 一篇学术综述，系统性地审视了基于LLM的自主智能体能够理解复杂输入、进行推理和规划、可靠使用工具并从错误中恢复的LLM系统，在明确任务后独立规划和操作，可根据环境反馈调整行为。的构建、应用和评估。

• Building effective agents (Anthropic) — An in-depth guide offering practical strategies for designing LLM-based agents, emphasizing starting with simple, composable patterns.

  构建有效的智能体（Anthropic） — 一份深入的指南，提供设计基于LLM的智能体的实用策略，强调从简单、可组合的模式开始。

• LLM Powered Autonomous Agents (Lilian Weng) — A comprehensive blog post exploring the architecture of autonomous LLM agents, covering both theory and implementation of core components.

  LLM驱动的自主智能体能够理解复杂输入、进行推理和规划、可靠使用工具并从错误中恢复的LLM系统，在明确任务后独立规划和操作，可根据环境反馈调整行为。（Lilian Weng） — 一篇全面的博客文章，探讨了自主LLM智能体的架构，涵盖了核心组件的理论和实现。

• What Are AI Agents? — An introductory article that provides a step-by-step guide to building an AI agent, focusing on business architecture.

  什么是AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.？ — 一篇介绍性文章，提供了构建AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.的分步指南，侧重于业务架构。

Framework Tutorials

Practical, hands-on tutorials for popular AI agent development frameworks and platforms.

针对流行的AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.开发框架和平台的实践性、动手教程。

• AutoGPT Guide — A step-by-step tutorial for setting up the full AutoGPT platform locally, covering both backend and frontend configurations.

  AutoGPT指南 — 一份在本地设置完整AutoGPT平台的逐步教程，涵盖后端和前端配置。

• CrewAI Quickstart Guide — A hands-on tutorial walking through building a multi-agent system using the CrewAI framework, demonstrating agent roles, task assignment, and orchestration.

  CrewAI快速入门指南 — 一个实践教程，引导使用CrewAI框架构建多智能体系统由多个相互协作的AI智能体组成的系统，能够处理复杂任务并通过智能体间的通信和协调实现更高级的自动化功能。，演示智能体角色、任务分配和编排。

• Haystack Tutorials — A collection of tutorials covering building, evaluating, and deploying agentic pipelines with Haystack.

  Haystack教程 — 一系列教程，涵盖使用Haystack构建、评估和部署智能体流程。

• Hugging Face smolagents Tutorials — Examples outlining best practices for building AI agents using the smolagents framework.

  Hugging Face smolagents教程 — 概述使用smolagents框架构建AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.最佳实践的示例。

• LangChain: Build an Agent — A hands-on guide demonstrating how to build an AI assistant capable of tool use with minimal setup.

  LangChain：构建智能体 — 一份实践指南，演示如何以最少的设置构建一个能够使用工具的AI助手。

• LlamaIndex Learning — A guide walking through building agentic applications using LlamaIndex, covering LLM basics, agent construction, workflows, and RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses. pipelines.

  LlamaIndex学习 — 一份指南，引导使用LlamaIndex构建智能体应用，涵盖LLM基础、智能体构建、工作流和RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses.流程。

• Microsoft AutoGen AgentChat Quickstart & Tutorial — A quick tutorial guiding through building an AI assistant using Microsoft's AutoGen AgentChat framework.

  微软AutoGen AgentChat快速入门与教程 — 一份快速教程，指导使用微软的AutoGen AgentChat框架构建AI助手。

• OpenAI Agents SDK Examples — A comprehensive collection of practical examples demonstrating how to build AI agents, organized into categories like agent patterns and tool integration.

  OpenAI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.SDK示例 — 一个全面的实用示例集合，演示如何构建AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.，按智能体模式、工具集成等类别组织。

• OpenAI Assistants API — A step-by-step tutorial on building AI assistants using OpenAI's Assistants API, covering assistant creation, tool integration, and conversation management.

  OpenAI Assistants API — 一份关于使用OpenAI的Assistants API构建AI助手的逐步教程，涵盖助手创建、工具集成和对话管理。

Evaluation Benchmarks

Standardized benchmarks are crucial for objectively measuring and comparing the capabilities of AI agents across diverse tasks and environments.

标准化的基准测试对于客观衡量和比较AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.在不同任务和环境中的能力至关重要。

Related Resources

Additional curated lists and summaries to further expand your learning journey.

额外的精选列表和摘要，以进一步扩展您的学习之旅。

• e2b-dev/awesome-ai-agents — A curated GitHub repository featuring a comprehensive list of AI autonomous agents and frameworks.

  e2b-dev/awesome-ai-agents — 一个精选的GitHub仓库，收录了全面的AI自主智能体能够理解复杂输入、进行推理和规划、可靠使用工具并从错误中恢复的LLM系统，在明确任务后独立规划和操作，可根据环境反馈调整行为。和框架列表。

• Mastering AI Agents: The 10 Best Free Courses, Tutorials & Learning Tools — A curated list of resources on AI Agents learning organized by skill level.

  掌握AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.：10个最佳免费课程、教程与学习工具 — 一份按技能水平组织的AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.学习资源精选列表。

Contributing

This resource list is actively maintained. Contributions are welcome to keep it current and comprehensive. Please review the contribution guidelines before submitting a pull request.

本资源列表持续维护中。欢迎贡献，以保持其时效性和全面性。提交拉取请求前，请先阅读贡献指南。

常见问题（FAQ）

有哪些适合初学者的AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.学习课程？

推荐微软的AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.入门课程（11节开源课）和AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.大师班（含完整代码演练），两者都从基础开始，涵盖工具集成、RAGRetrieval-Augmented Generation - an AI framework that combines information retrieval with language generation to produce more accurate and contextually relevant responses.等实践内容。

如何系统评估自主AI/LLM智能体的性能？

本资源集合专门设有“评估基准用于系统评估和比较RAG模型性能的标准数据集和评测指标。”分类，提供系统化的评估框架和指标，帮助专业人士对智能体的性能进行严格、可量化的测试与分析。

哪里能找到构建AI智能体An autonomous intelligent system that perceives its environment, makes decisions, and executes tasks, characterized by autonomy and adaptability.的框架教程和概念指南？

资源集合包含“框架教程”和“概念指南”部分，提供如LangChain、CrewAI等框架的实践教程，以及OpenAI、Anthropic等发布的架构设计与策略指南。