
awesome-artificial-intelligence
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
Install with your AI
Paste into Claude Code, Cursor, or any agent — it reads the repo and wires the tool into your project.
Install and set up awesome-artificial-intelligence (git-clone project) into my current project. Found on https://claudeers.com/awesome-artificial-intelligence Repo: https://github.com/owainlewis/awesome-artificial-intelligence Homepage/docs: — Detected install method: git-clone → git clone https://github.com/owainlewis/awesome-artificial-intelligence Category: education. Platforms: cli, api, web. Read the repo's README for exact setup and env vars, then install it and wire it into my project. Claudeers Health Verdict: slowing; community-verified: false. Confirm the source before running anything.
git clone https://github.com/owainlewis/awesome-artificial-intelligence
// compatibility
| Platforms | cli, api, web |
|---|---|
| Operating systems | — |
| AI compatibility | claude |
| License | MIT |
| Pricing | open-source |
| Language | — |
Awesome Artificial Intelligence
A curated collection of must-use, actively maintained resources for building and shipping AI systems.
Focus: AI engineering (RAG, agents, evals, guardrails, deploy) plus the best books, guides, papers, and a carefully selected set of tools.

📚 Learn
Deep, durable knowledge — still valuable five years from now.
Books
Modern & Practical
- Designing Machine Learning Systems — Scalable, maintainable ML pipelines (Chip Huyen).
- AI Engineering — End-to-end AI product building (Chip Huyen).
- Build a Large Language Model from Scratch — Transformers in raw PyTorch, layer by layer (Sebastian Raschka).
- Hands-On Large Language Models — Visual + practical guide to LLM applications (Jay Alammar, Maarten Grootendorst).
- LLM Engineer's Handbook — Production LLMOps: fine-tuning, quantization, serving (Labonne, Iusztin).
- The 100-Page Language Models Book — Concise, math-grounded path from n-grams to transformers (Andriy Burkov).
- Generative Deep Learning (2nd Edition) — GANs, VAEs, diffusion models (David Foster).
Foundational
- Artificial Intelligence: A Modern Approach — The canonical AI theory text (Russell, Norvig).
- Deep Learning — Mathematical foundations of neural networks (Goodfellow, Bengio, Courville).
- Deep Learning: Foundations and Concepts — Bishop's 2024 update; probability-grounded modern DL (Bishop & Bishop).
- Understanding Deep Learning — Math + intuition + Python notebooks (Simon Prince).
- Speech and Language Processing (3rd Edition) — The NLP reference, kept current through the deep learning era (Jurafsky, Martin).
- Reinforcement Learning: An Introduction (2nd Edition) — RL foundations (Sutton, Barto).
Courses
Beginner
Intermediate / Advanced
Focused
- DeepLearning.AI Short Courses
- Google DeepMind — Introduction to Reinforcement Learning
- Karpathy — Neural Networks: Zero to Hero
Landmark Papers
Research that shaped modern AI — worth reading to understand the "why" behind today's architectures.
- Attention Is All You Need — Transformer architecture.
- Scaling Laws for Neural Language Models — Model/data/compute scaling.
- Language Models are Few-Shot Learners — GPT-3 capabilities.
- Constitutional AI — Safer model alignment.
🛠 Build
The toolchain for building with AI. Personal note: you don't need tons of frameworks — start with simple LLM calls and work up.
Guides & Playbooks
- Building Effective Agents (Anthropic) — ⭐ Patterns, pitfalls, and tradeoffs for designing AI agents.
- OpenAI Agents Guide — Practical guide on building agents.
- Google AI Agents Paper — Practical guide to building AI agents from Google.
- Google Agents Companion Paper — Companion guide from Google.
- OpenAI Cookbook — Example code, recipes, and best practices for working with OpenAI APIs.
- LLM Engineer Handbook — A goldmine of useful links for AI engineers.
Frameworks
- PocketFlow — Extremely minimalist AI agent framework in just 100 lines of code. Fantastic way to learn.
- Google ADK — Google's Agent Development Kit (Python, Java). Great local development experience + A2A + MCP.
- Pydantic-AI — Typed, structured LLM orchestration framework built on Pydantic models for safe, predictable outputs.
- LangGraph — Build multi-agent workflows with stateful graphs on top of LangChain.
- CrewAI — Agent orchestration with structured tasks and human-in-the-loop controls.
- AutoGen — Microsoft's framework for multi-agent conversation and collaboration.
- LlamaIndex — Data framework for ingesting, indexing, and querying private data with LLMs.
- Haystack — Open-source search/RAG framework with modular pipelines.
- Docling — Great library for ingesting any kind of document for RAG ⭐
Evals
- OpenAI Evals — OpenAI's framework for writing evals.
IDEs
- Cursor — LLM-powered IDE for multi-file edits and codebase-aware chat.
- GitHub Copilot — In-IDE code completion, chat, and refactors.
🤖 Agents
Harnesses that turn LLMs into autonomous workers. The model is swappable; the harness is the product.
Coding
For live capability comparison, see Terminal-Bench and SWE-bench.
- Claude Code — Anthropic's CLI agent; multi-file codebase refactoring with long context.
- Codex CLI — OpenAI's Rust-based local terminal agent; lightweight and fast.
- Gemini CLI — Google's official open-source terminal agent; long-context repo exploration.
- Cursor CLI — Cursor's terminal-native agent with sandboxed permissions.
- Aider — Git-integrated pair programming with surgical edits and undo.
- OpenCode — Provider-agnostic terminal harness with a strong TUI.
- OpenHands — Open-source autonomous SWE platform; browser + shell + editor loop.
- Cline — Open-source agentic IDE extension with strong multi-provider support.
- Continue — Open-source IDE + CLI assistant with source-controlled rules.
- Goose — Block's extensible, MCP-driven local agent.
- Factory Droid — Benchmark-leading multi-model harness with BYOK local execution.
- Amp — Sourcegraph's commercial agentic coding tool with strong product UX.
- Mistral Vibe — Mistral's agentic coding CLI, powered by Devstral.
- Qwen Code — Alibaba's terminal coding agent, optimized for Qwen models.
- Pi — Highly customizable terminal harness; minimal base prompt, extension-driven.
- Nanocoder — Private, local-first agent for Ollama and LM Studio.
- Kilo CLI — Multi-mode agent with a unified gateway to 500+ models.
🧠 Models
State-of-the-art models by modality.
💬 Language
The major frontier labs.
- ChatGPT — Best for general reasoning, tool use, and the broadest ecosystem.
- Claude — Best for long-context analysis, coding, and structured thinking.
- Gemini — Best for multimodal tasks and Google ecosystem integration.
- Grok — Best for real-time information via X and very long context.
- Llama — Best open-weight family for self-hosting and fine-tuning.
- Mistral — Best for lightweight, high-performance open-weight models.
- DeepSeek — Best for cost-efficient reasoning with open weights.
- Qwen — Best for multilingual and Chinese-first applications.
- Kimi — Best for long-context instruction following.
- GLM — Frontier-tier Chinese model with open weights.
- Cohere — Best for enterprise LLMs with strong retrieval-augmented generation APIs.
🖼 Image
- GPT Image — OpenAI's integrated image generation with near-perfect text rendering.
- Midjourney — Artistic and photorealistic images.
- Adobe Firefly — Integrated into Creative Cloud; commercial-safe.
- Ideogram — Precise, legible text in generated images.
- Flux — High-res, prompt-editable, open-weight images.
🎥 Video
- Google Veo — High-quality video with synchronized audio.
- Runway — Video editing + generation with granular creative control.
- Kling — Cinematic, realistic video generation.
🎙 Audio
- ElevenLabs — High-quality text-to-speech and voice cloning.
- Suno — AI music from text prompts.
📊 Compare
Live benchmarks, pricing, and the latest model versions.
- OpenRouter — Unified API + live pricing across ~300 models.
- LMArena — Human-preference Elo rankings for text, image, and video.
- Artificial Analysis — Speed, price, and quality benchmarks across providers.
📡 Follow
Stay current without drowning in noise.
Newsletters
// faq
What is awesome-artificial-intelligence?
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.. It is open-source on GitHub.
Is awesome-artificial-intelligence free to use?
awesome-artificial-intelligence is open-source under the MIT license, so it is free to use.
What category does awesome-artificial-intelligence belong to?
awesome-artificial-intelligence is listed under other in the Claudeers registry of Claude-compatible tools.
// embed badge
[](https://claudeers.com/awesome-artificial-intelligence)
// retro hit counter
[](https://claudeers.com/awesome-artificial-intelligence)
// reviews
// guestbook
// related in Education & Learning
Skills for Real Engineers. Straight from my .claude directory.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Learn it. Build it. Ship it for others.
A collection of learning resources for curious software engineers