LLMRepos·Roadmaps LLM projects

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

Mastering Applied AI, One Concept at a Time

A complete, structured hub for learning Artificial Intelligence — covering AI, Machine Learning, Deep Learning, and Data Science with books, roadmaps, and curated resources from beginner to advanced.

The roadmap of long-horizon agents

Learning Large Language Model (LLM）(大语言模型学习)

🔥机器学习/深度学习/Python/大模型/多模态/LLM/deeplearning/Python/Algorithm interview/NLP Tutorial

Ultimate AI Engineer Roadmap 2026 - built specifically for your context as an AI Architect building PrinceSinghAI, PrinceSinghDev, Multi-LLM orchestration, RoadmapAI, CodeLLM, and AskAI, Global AI Search

A 10-week, 30-minutes-a-day roadmap for LLM inference serving and optimization. vLLM, SGLang, quantization, speculative decoding, benchmarking.

AI/ML Pentesting Roadmap for Beginners

A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient in all aspects of machine learning, including data collection and preprocessing, model development, deployment, and maintenance.

🔧 The open guide to Harness Engineering — concepts, tutorials, papers, tools, and resources for building and managing AI agent runtimes.

Use agent to learn agent - A skeleton course on how to design, build, and operate production AI agents

A complete roadmap to master LLMs from absolute beginners to advanced

🎯 从零基础到 AI Agent 全栈工程师 · 110 个详细教程 · 58 万字 · 400+ GitHub 项目精选 · Obsidian 友好 · 中文

Master AI inference, AI agent harness systems, and hardware engineering — then design a physical AI chip. That is the goal.

The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.

Comprehensive guide to AI agent engineering: how 30+ frameworks actually work under the hood. Context rot, compaction, system prompt assembly, SOUL.md, agent loops, memory systems, tool sprawl, MCP, progressive disclosure, multi-agent orchestration, Plan/Act, episodic memory. Code examples throughout. Pick the right stack, avoid the common traps