Curated collection of the best MIT-licensed AI, LLM, and Agent courses from GitHub
Everything you need to know about agentic AI in the real world. Covers agents, tools, RAG, MCP, planning, memory, and multi-agent systems.
Start Learning →Comprehensive guides, papers, and resources for prompt engineering. Covers techniques like Zero-shot, Few-shot, Chain-of-Thought, ReAct, and more for all major LLMs.
Start Learning →Complete roadmap to master LLMs with Colab notebooks. Covers fundamentals, fine-tuning, RLHF, RAG, agents, quantization, and deployment.
Start Learning →Collection of 30+ practical LLM applications with AI Agents and RAG. Uses OpenAI, Anthropic, Gemini, and open-source models. Real-world, ready-to-run projects.
Start Learning →In-depth tutorials on LLMs, RAG, and real-world AI agent applications. Production-ready implementations with OCR, vision models, and local AI apps.
Start Learning →Introduction to RAG (Retrieval-Augmented Generation) with LangChain & Ollama. Includes PDF guide and hands-on Jupyter notebooks for practical learning.
Start Learning →Complete LangChain tutorial covering models, chains, RAG, and agents. Video course with code examples for quick learning. Perfect for getting started with LangChain.
Start Learning →The simplest beginner's guide to prompt engineering. Learn universal principles with simple analogies and copy-paste examples. No tech skills needed.
Start Learning →Curated collection of 500+ AI agent use cases across industries with implementation links. Great for finding practical applications and project ideas.
Start Learning →Curated list of courses, guides, and resources for learning to build autonomous LLM agents. Comprehensive awesome-list compilation.
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