{"data":{"slug":"wethinkin-aigc-interview-book","name":"AIGC-Interview-Book","tagline":"Three Years of Interviews Five Years of Practice The Ultimate Guide to AIGC Interview LLMs Interview AI Agent Interview Deep Learning Interview Algorithm Engineer Interview","github_url":"https://github.com/WeThinkIn/AIGC-Interview-Book","owner":"WeThinkIn","repo":"AIGC-Interview-Book","owner_avatar_url":"https://avatars.githubusercontent.com/u/48612300?v=4","primary_language":null,"stars":4382,"forks":449,"topics":["ai-agent","aigc","computer-vision","deep-learning","interview","interview-preparation","interview-questions","interviews-solutions","large-language-models","machine-learning","natural-language-processing","openclaw","stable-diffusion","transformer"],"archived":false,"github_pushed_at":"2026-08-16T16:37:06+00:00","maintenance_label":"Very active","stars_delta_30d":259,"url":"https://www.graphcanon.com/tools/wethinkin-aigc-interview-book","markdown_url":"https://www.graphcanon.com/tools/wethinkin-aigc-interview-book.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/wethinkin-aigc-interview-book","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=wethinkin-aigc-interview-book","description":"【三年面试五年模拟】AIGC/LLM/AI Agent算法工程师面试资源平台。涵盖AIGC、LLM大模型、AI Agent、具身智能、传统深度学习、计算机视觉、自然语言处理、自动驾驶、机器学习、强化学习、大数据挖掘、世界模型、元宇宙、AGI等AI行业面试笔试干货经验与核心跨周期知识。","homepage_url":"https://wethinkin.github.io/AIGC-Interview-Book/","license":"GPL-3.0","open_issues":0,"watchers":24,"ai_summary":"A comprehensive guide for interview and preparation in the fields of AIGC, large language models (LLMs), AI agents, traditional deep learning, self-driving technology, machine learning, computer vision, natural language processing, reinforcement learning, big data mining, embodied intelligence, metaverse, and AGI.","readme_excerpt":"
\n\n# 🔥【三年面试五年模拟】AIGC/LLM/AI Agent算法岗/开发岗的面试求职秘籍\n\n【Three Years of Interviews, Five Years of Practice】The Ultimate Guide to **AIGC Interview、LLMs Interview、AI Agent Interview、Deep Learning Interview、Algorithm Engineer Interview**\n\n**AI行业最前沿、最全面、最本质、最跨周期的学习、研究、面试、职业生涯成长平台**，涵盖AIGC面试、LLM大模型面试、AI Agent面试、传统深度学习AI岗位面试、AI应用开发面试、AI应用商业化落地、AI职业生涯发展规划等。\n\n在这里我们不仅告诉大家 AI 技术是什么，更告诉大家哪些AI技术与AI认知值得长期投入，为什么值得投入，以及如何把握对AI技术的本质判断&学习能力，并在此基础上做出正确的职业生涯决策。我们追踪AI技术发展，但不是所有AI技术都具备跨周期价值；真正能够进入本项目平台作为核心内容的，是经过工业界、学术界、竞赛界、投资界以及应用界持续评估与检验的。\n\n
\n\n# \n\n🏆**AIGC算法岗方向：** 涵盖AIGC、LLM大模型、AI Agent、具身智能、传统深度学习、自动驾驶、机器学习、计算机视觉、自然语言处理、强化学习、大数据挖掘、世界模型、元宇宙、AGI等。\n\n🏆**AIGC开发岗方向：** 涵盖FDE、Python、Java、C/C++、Go、嵌入式、前端、后端、测试、运维、设计、售前等。\n\n🚀**本项目凝聚了AIGC时代众多一线AIGC/LLM/AI Agent算法专家的行业经验与深度洞察**，涵盖AIGC/LLM/AI Agent等前沿AI技术的完整知识架构、AI大厂内推、AI面试经验、AI公司指南/辛秘、AI面试准备、AI薪资爆料、AI刷题指南、AI求职答疑、AI职业生涯发展规划等干货资源。本项目平台的核心内容均提炼于编者专家们在AI行业中的工作、研究、竞赛经验以及对互联网大厂/AI明星公司的AI岗位笔试/面试题。\n\n💡**本项目平台也可作为高等学府AIGC、LLM、AI Agent相关专业的研究、教学、竞赛以及学习的核心参考平台**；还可为AIGC、LLM、AI Agent、传统深度学习以及自动驾驶领域的初、中级技术人员提供技术思路参考，**尤其适合AIGC/LLM/AI Agent求职者和提供相关AIGC/LLM/AI Agent岗位的面试官进行深入研读**。\n\n👍**本项目的持续构建/升级/维护十分不易，希望大家能多多star～。Star本项目，你就获得了0.5个心仪的offer；再分享本项目，你就获得了0.75个心仪offer！在这里，Rocky祝大家求职顺利、工作顺利、职业生涯顺利！**\n\n## 📖目录\n\n### 🧱核心知识板块\n\n- :star: [AI行业面试求职经验指南（包含简历模版、求职攻略、面试经验、面试技巧等通用AI岗位面试技巧）](AI行业面试求职经验指南)\n- :art: [AIGC图像创作&AI绘画基础](AIGC图像创作&AI绘画基础)\n- :clapper: [AI视频基础](AI视频基础)\n- :sparkler: [大模型基础](大模型基础（精华版）)\n- :trident: [AI多模态基础](AI多模态基础)\n- :video_game: [AI Agent基础](AI%20Agent基础)\n- :shipit: [AI数字人基础](AI数字人基础)\n- :abacus: [数学&物理本质原理基础](数学&物理本质原理基础)\n- :closed_book: [深度学习基础](深度学习基础)\n- :blue_book: [机器学习基础](机器学习基础)\n- :european_castle: [模型部署基础](模型部署基础)\n- :stars: [经典模型](经典模型)\n- :snake: [编程基础：Python](编程基础：Python)\n- :bar_chart: [编程基础：C和C++](编程基础：C和C++)\n- :boom: [大厂高频面试题（实时更新）](大厂高频面试题（实时更新）)\n- :battery: [数据结构&算法基础](数据结构&算法基础)\n- :computer: [计算机基础](计算机基础)\n- :chart_with_upwards_trend: [AI行业职业生涯开放性问题](AI行业职业生涯开放性问题)\n- [2026年AI算法岗求职群&学习交流社区](https://mp.weixin.qq.com/s/ssEJjHBoJDB4y5CfQIWYvw)\n\n### 🧭热门AI学习教程精选\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
热门教程精选
2026 AI Agent 岗面试 50 问
Agent 本质、工具协议、Memory、评测与平台设计		多模态算法岗 30 天复习路线
视觉语言模型、模态对齐、训练微调与面试表达		大模型面试最高频 100 问
架构、训练、后训练、RAG、推理与评测主干
AI 算法岗薪资与岗位技术栈地图
岗位方向、技术栈、薪资认知与投递判断		从传统 CV 转 AIGC 的最短路径
复用 CV 能力，补齐生成模型、多模态与大模型主干		30 天 AI 算法岗冲刺路线
基础、方向、项目、表达和模拟面试快速闭环
60 天大模型算法岗系统路线
从 Transformer 到训练、对齐、评测、部署与应用		AI Agent 工程岗面试路线
工作流、工具、MCP、Memory、AgentOps 和系统设计		多模态算法岗面试路线
多模态架构、编码映射、训练评测与岗位题型
AIGC 图像/视频生成算法岗路线
扩散模型、可控生成、视频生成与工程实践		模型部署与推理优化路线
推理框架、量化压缩、吞吐延迟与性能调优		传统 CV/NLP 转大模型路线
能力迁移、Transformer、后训练、RAG 与生成式评测
开发岗转 AI 应用工程师路线
Prompt、RAG、Agent、评测、部署与服务化		校招 AI 算法岗求职路线
岗位画像、项目证据、简历表达与校招节奏		社招 AI 算法岗跳槽路线
能力盘点、简历升级、岗位匹配与面试复盘
\n\n## 💎加入 AIGCmagic 进阶服务社区（实习、秋招、春招、校招、社招）\n\n《三年面试五年模拟》源自 AIGCmagic 社区的长期积累。需要更多AI行业职业生涯规划、求职招聘、课程培训、个性化定制服务的读者朋友们，可以进入进阶服务社区，我们将进一步提供：\n\n- **答疑**：技术问题、面试准备与求","github_created_at":"2023-10-14T16:15:40+00:00","created_at":"2026-07-07T17:35:33.372106+00:00","updated_at":"2026-08-17T18:01:36.162683+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"ai-agent","name":"ai-agent"},{"slug":"aigc","name":"aigc"},{"slug":"computer-vision","name":"computer-vision"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"interview-preparation","name":"interview-preparation"},{"slug":"large-language-models","name":"large language models"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"natural-language-processing","name":"natural-language-processing"}],"trust":{"provenance":{"is_fork":false,"github_id":704959035,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-17T18:01:33.872Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1,"last_release_at":null,"stars_delta_30d":259,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:05:39.683Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-17T18:01:35.092Z"},"license_spdx":{"value":"GPL-3.0","source":"github.license","observed_at":"2026-08-17T18:01:35.092Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Use when preparing for highly specialized roles such as AIGC algorithm engineer or developer positions.","Prefer if you need detailed insights into the latest industry interview questions from leading tech companies."],"when_not_to_use":["Avoid if your role is less specialized and focuses more on broad machine learning and data engineering tasks where a general resource might suffice.","Do not use if you prefer resources without the commercial aspects, such as paid community access or additional fee-based content."],"source":"enrich:decision_facts","observed_at":"2026-07-14T19:47:29.687Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"AIGC-Interview-Book is a comprehensive guide tailored specifically for interviews in AIGC, large language models (LLMs), AI agents, deep learning and related fields."}]}}