LLM Interview Preparation LLM Tools

Repositories containing interview questions, answers, and study guides specifically for LLM/AI engineer and ML roles. Does NOT include general career advice, resume tools, or job application automation platforms.

There are 29 llm interview preparation tools tracked. 2 score above 50 (established tier). The highest-rated is datawhalechina/daily-interview at 54/100 with 3,565 stars.

Get all 29 projects as JSON

curl "https://pt-edge.onrender.com/api/v1/datasets/quality?domain=llm-tools&subcategory=llm-interview-preparation&limit=20"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

#	Tool	Score	Tier	Stars	Language
1	datawhalechina/daily-interview Datawhale成员整理的面经，内容包括机器学习，CV，NLP，推荐，开发等，欢迎大家star	54	Established	3,565	—
2	KalyanKS-NLP/LLM-Interview-Questions-and-Answers-Hub 100+ LLM interview questions with answers.	52	Established	809	—
3	jackaduma/awesome_LLMs_interview_notes LLMs interview notes and answers:该仓库主要记录大模型（LLMs）算法工程师相关的面试题和参考答案	44	Emerging	1,310	—
4	whaleonearth/MLE-DS-Interview-Prep-Guide This repo is meant to serve as a detailed guide for Machine Learning/AI interviews.	44	Emerging	288	—
5	wdndev/llm_interview_note 主要记录大语言大模型（LLMs）算法（应用）工程师相关的知识及面试题	40	Emerging	13,130	HTML
6	Picovoice/pico-cookbook Recipes for on-device voice AI and local LLM	40	Emerging	107	C
7	ningg/Machine-Learning-Q-and-AI 大模型技术30讲（原版），30 Essential Questions and Answers on Machine Learning and AI，百面大模型	34	Emerging	29	Python
8	chensi-cs/LLM-Interview-Guidebook 本仓库是一份面向大模型算法工程师的面试宝典，系统梳理了大模型的核心知识点，帮助读者快速掌握大模型面试中的重点和难点	30	Emerging	45	—
9	Joining-AI/LLM_Interview_Prepare 本仓库是关于大模型面试中常见面试试题和面试经验的整理。这里收集了各类与大模型相关的面试题目，并提供详细的解答和分析。本仓库由上海交大交影社区维护	28	Experimental	119	HTML
10	AIR-hl/llm-interview-code LLM面试常见手撕合集	28	Experimental	248	Jupyter Notebook
11	zs1314/Grain-Rain-Intelligence-Valley 【Engineering Project】Offical Pytorch Code for "Grain Rain Intelligence Valley"	23	Experimental	5	Python
12	shaoxueheng/AI-LLM-Practice AI大模型实战：从零基础到项目落地	23	Experimental	1	HTML
13	sreekanth-madisetty/Awesome-LLM-Interview-Questions A curated collection of interview questions and expert answers focused on...	22	Experimental	16	—
14	cheaaaaa/ai-cognition-notes 算法模型学习、源码阅读与 AI 认知文章仓库	22	Experimental	—	Python
15	bnovik0v/llm-interview-questions 430 technical interview questions with answers for LLM Researcher, LLM...	22	Experimental	—	—
16	krish-mm/cookbookLM An Open Source alternative of Google's NotebookLM	18	Experimental	3	TypeScript
17	CycloneBoy/llm_interview llm interview skills 大模型面试技能	17	Experimental	2	HTML
18	FredericVAN/LLM-Coding-Interview-tutorial LLM Coding Interview Preparation 手撕代码系列	17	Experimental	2	Jupyter Notebook
19	Harsh-Avinash/Caduceus Infinite power but in a pendrive	16	Experimental	4	Jupyter Notebook
20	Lvyizhuo/Alibaba-ACACertification-LLM 阿里云大模型工程师 ACA 认证-教程-笔记-思维导图	15	Experimental	1	HTML
21	Greebbie/LLM-Agent-Core_Concept_Code Designed essential LLM course for zero to LLM, a tutorial to follow up....	15	Experimental	6	Jupyter Notebook
22	DolbyUUU/Awesome-LLM-Interview-Questions-and-Answers 大模型算法工程师、大模型Agent开发工程师面试：常见题目和答案	14	Experimental	30	—
23	Adarsh-Khatri/ai-ml-interview-prep Structured AI/ML/LLM interview preparation with in-depth explanations and intuition	14	Experimental	—	—
24	DjordjeDacovic/vmux-examples 🚀 Run Python scripts in the cloud with vmux, simplifying execution for short...	14	Experimental	—	Python
25	pchemguy/LLM101 Notes on LLM learning.	14	Experimental	—	—
26	sudhanshukuumar/LLM-Algorithm-Intern-Guide 📚 Enhance your interview preparation for LLM algorithm internships with...	14	Experimental	—	—
27	FromZeroToFanatic/LLM_Practical_Implementation_Demo4 大模型实战学习路线阶段4：大模型应用实战（基于langchain搭建LLMs应用）与实战	11	Experimental	7	—
28	M-R-Saad/Learning-DL 🧠 Deep learning algorithms implemented from scratch using only NumPy — no...	11	Experimental	—	Jupyter Notebook
29	FromZeroToFanatic/LLM_Practical_Implementation_Demo3 大模型实战学习路线阶段3：大模型应用实战（prompt提示工程深度解析及高级用法）与实战	10	Experimental	4	—

Comparisons in this category

awesome_LLMs_interview_notes and llm_interview_note (44 vs 40) LLM-Interview-Questions-and-Answers-Hub and awesome_LLMs_interview_notes (52 vs 44) awesome_LLMs_interview_notes and LLM_Interview_Prepare (44 vs 28) awesome_LLMs_interview_notes and LLM-Interview-Guidebook (44 vs 30) awesome_LLMs_interview_notes and Awesome-LLM-Interview-Questions (44 vs 22) LLM-Interview-Questions-and-Answers-Hub and Awesome-LLM-Interview-Questions (52 vs 22) LLM-Interview-Questions-and-Answers-Hub and llm-interview-questions (52 vs 22)