“The best way to learn AI is to start building. These resources will guide your journey.”
In my ongoing effort to keep the AI Resources list focused on production-ready tools and frameworks, I’ve removed 44 collection-type projects—courses, tutorials, awesome lists, and cookbooks.
These resources aren’t gone—they’ve been moved here. This post is a curated collection of those educational materials, organized by type and topic. Whether you’re a complete beginner or an experienced practitioner, you’ll find something valuable here.
Why Remove Collections from AI Resources?
My AI Resources list now focuses on concrete tools and frameworks—projects you can directly use in production. Collections, while valuable, serve a different purpose: education and discovery.
By separating them, I:
- Keep the resources list actionable and focused
- Create a dedicated space for learning materials
- Make it easier to find what you need
📚 Awesome Lists (14 Collections)
Awesome lists are community-curated collections of the best resources. They’re perfect for discovering new tools and staying updated.
Must-Explore Awesome Lists
- Models, tools, tutorials, and research papers
- Great for: Comprehensive overview of generative AI landscape
- LLM resources: papers, tools, datasets, applications
- Great for: Deep dive into large language models
- Practical LLM applications, RAG examples, agent implementations
- Great for: Real-world implementation examples
- Claude Code commands, files, and workflows
- Great for: Maximizing Claude Code productivity
- MCP servers for modular AI backend systems
- Great for: Building with Model Context Protocol
Specialized Awesome Lists
- Awesome ChatGPT Prompts - Prompt examples for various scenarios
- Awesome LLM Apps - LLM applications with code examples
- Awesome Multimodal LLM - Multimodal model resources
- Awesome MCP Clients - MCP client tools and SDKs
- Awesome Claude Skills - Claude Skills and workflows
- Awesome GitHub Copilot - Copilot customizations
- Awesome Nano Banana Pro - Image model prompts and examples
- Awesome SaaS - AI platform templates
- Awesome Claude Code Subagents - Claude Code subagents
🎓 Courses & Tutorials (9 Curricula)
Structured learning paths from universities and tech companies.
Microsoft’s AI Curriculum
- 12 weeks, 24 lessons covering neural networks, deep learning, CV, NLP
- Great for: Complete AI foundation
- Format: Lessons, quizzes, projects
Machine Learning for Beginners
- 12-week, 26-lesson curriculum on classic ML
- Great for: ML fundamentals without deep math
- Format: Project-based exercises
- 18 lessons on building GenAI applications
- Great for: Practical GenAI development
- Format: Hands-on projects
- 11 lessons on agent systems
- Great for: Understanding autonomous agents
- Format: Project-driven learning
- Optimization, deployment, and real-world Edge AI
- Great for: On-device AI applications
- Format: Practical tutorials
- Model Context Protocol curriculum
- Great for: Building with MCP
- Format: Cross-language examples and labs
Official Platform Courses
- Free courses on LLMs, deep RL, CV, audio
- Great for: Hands-on Hugging Face ecosystem
- Format: Interactive notebooks
- Runnable examples using OpenAI API
- Great for: OpenAI API best practices
- Format: Code examples and guides
- Basics to advanced deep learning
- Great for: PyTorch mastery
- Format: Comprehensive tutorials
🍳 Cookbooks & Example Collections (5 Collections)
Practical code examples and recipes.
- Notebooks and examples for building with Claude
- Great for: Anthropic Claude integration
- Format: Jupyter notebooks
- Practical AI cookbook with Jupyter notebooks
- Great for: Open models and tools
- Format: Hands-on examples
- Training and fine-tuning examples
- Great for: Fine-tuning workflows
- Format: Platform-specific recipes
- Examples for building LLM apps
- Great for: LLM application development
- Format: Recipes and tutorials
- 6-week course on RAG systems
- Great for: Production-ready RAG
- Format: Project-based learning
📖 Guides & Handbooks (5 Resources)
In-depth guides on specific topics.
- Comprehensive prompt engineering resources
- Great for: Mastering prompt design
- Format: Guides, papers, lectures, notebooks
- LLM evaluation best practices from Hugging Face
- Great for: Assessing LLM performance
- Format: Practical guide
- Design and optimize context beyond prompt engineering
- Great for: Advanced context management
- Format: Practical handbook
- Template and guide for context engineering
- Great for: Providing project context to AI assistants
- Format: Template + guide
- 5-step prompt template for building MVPs with LLMs
- Great for: Rapid prototyping with AI
- Format: Workflow template
🗂️ Template & Workflow Collections
Reusable templates and workflows.
- Code templates for various programming scenarios
- Great for: Claude AI development
- Format: Template collection
- 2,000+ professionally organized n8n workflows
- Great for: Workflow automation
- Format: Searchable catalog
- Community-driven reusable workflow templates
- Great for: Workflow import and versioning
- Format: Template catalog
📊 Research & Evaluation
Academic and evaluation resources.
- Curated list of LLM systems papers
- Great for: Research on training, inference, serving
- Format: Paper collection
- LLM providers with free/trial API access
- Great for: Experimentation without cost
- Format: Provider list
🎨 Other Notable Resources
System Prompts and Models of AI Tools
- Community-curated collection of system prompts and AI tool examples
- Great for: Prompt and agent engineering
- Format: Resource collection
- EPFL Machine Learning Course
- Great for: Academic ML foundation
- Format: Lectures, labs, projects
- ML engineering open-book: compute, storage, networking
- Great for: Production ML systems
- Format: Comprehensive guide
- Build low-latency voice agents
- Great for: Voice AI applications
- Format: Hands-on course
- Build a working LLM from first principles
- Great for: Understanding LLM internals
- Format: Repository + book materials
💡 How to Use This Collection
For Complete Beginners
- Start with: Microsoft’s AI for Beginners
- Practice with: PyTorch Tutorials
- Explore: Awesome AI Apps for inspiration
For Developers
- Build skills: OpenAI Cookbook + Claude Cookbooks
- Find tools: Awesome Generative AI + Awesome LLM
- Learn workflows: n8n Workflows Catalog
For Researchers
- Stay updated: Awesome Generative AI + LLMSys PaperList
- Deep dive: Awesome LLM
- Implement: Hugging Face Cookbook
For Product Builders
- Find examples: Awesome AI Apps
- Learn workflows: n8n Workflows Catalog
- Study patterns: Awesome LLM Apps
🔄 What Was NOT Removed
Agent frameworks and production tools remain in the AI Resources list, including:
- AutoGen - Microsoft’s multi-agent framework
- CrewAI - High-performance multi-agent orchestration
- LangGraph - Stateful multi-agent applications
- Flowise - Visual agent platform
- Langflow - Visual workflow builder
- And 80+ more agent frameworks
These are functional tools you can use to build applications, not educational collections. They belong in the AI Resources list.
📝 Summary
I removed 44 collection-type projects from the AI Resources list to keep it focused on production tools:
- 14 Awesome Lists - Discover new tools and stay updated
- 9 Courses & Tutorials - Structured learning paths
- 5 Cookbooks - Practical code examples
- 5 Guides & Handbooks - In-depth resources
- 4 Template Collections - Reusable workflows
- 7 Other Resources - Research and evaluation
These resources remain incredibly valuable for learning and discovery. They just serve a different purpose than the production-focused tools in my AI Resources list.
Next Steps:
- Bookmark this post for future reference
- Explore the AI Resources list for production tools (agent frameworks, databases, etc.)
- Check out my blog for more AI engineering insights
Acknowledgments: This collection was compiled during my AI Resources cleanup initiative. Special thanks to all the maintainers of these awesome lists, courses, and collections for their invaluable contributions to the AI community.
