LLM Introduction
A comprehensive intro to Large Language Models by Andrej Karpathy.
A comprehensive intro to Large Language Models by Andrej Karpathy.
Build a GPT-style model from scratch in Python.
Andrew Ng on the future of agentic workflows.
Deep dive into testing and refining AI agents.
Anthropic's guide to reliable agent design.
Using Model Context Protocol for smarter agents.
Live coding a custom agent framework.
Series on philosophical approaches to AI alignment.
The best AI coding tools for developers that are actually useful.
Essential AI tools for modern software development.
NEW Agentic Coding LLM with vision - opensource and powerful.
How to build apps using vibe coding and no code tools.
Framework for programming—not prompting—language models.
Comprehensive guide for building intelligent, interactive AI systems.
12 Lessons to Get Started Building AI Agents
Guides, papers, lessons, notebooks and resources for prompt engineering.
Official code repo for the O'Reilly Book - 'Hands-On Large Language Models'
Learn how to design, develop, deploy and iterate on production-grade ML apps.
Practical LLM-powered apps and agent examples.
A one stop repository for generative AI research updates and tools.
Summaries and resources for Designing Machine Learning Systems book.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all.
Course to get into Large Language Models (LLMs) with roadmaps.
Configuration files that enhance Cursor AI editor experience with custom rules and behaviors.
Standards for building agents, better.
Specialized agents designed to power your brainstorming sessions.
Google's Agent Development Kit sample for deep search functionality.
Neo4j-powered task management system for LLM Agents with three-tier architecture.
Google's comprehensive framework for agentic systems.
Practical implementation companion to the whitepaper.
Best practices for reliable agent orchestration.
Optimizing prompts and context for Claude.
Strategic guide to enterprise agent deployment.
Best practices for documenting AI agents from 2500+ repos.
Guide on context engineering, sessions, and memory management for AI agents.
Introducing Nested Learning for continual learning in machine learning systems.
A comprehensive modern textbook on Deep Learning.
Code your own LLM from the ground up.
Practical patterns for production LLM systems.
Complete reference for autonomous agent architecture.
Hands-on guide to agent-based application dev.
Mastering the Model Context Protocol.
Foundations of engineering robust AI systems.
Synergizing reasoning and acting in language models.
Interactive simulacra of human behavior.
Language models can teach themselves to use tools.
Eliciting reasoning in large language models.
Multi-agent systems extending LLMs from independent single-model reasoning.
Exploring the definition and research landscape of Artificial General Intelligence.
Comprehensive survey on deep research methodologies and AI-powered research.
Benchmarking LLM agent test-time learning with self-evolving memory.
Decision-making in natural and artificial multi-agent systems.
Framework for nested learning in continual learning systems.
The foundational Transformer architecture paper from NeurIPS 2017.
Official course on building agents with Hugging Face.
Learn to build rich context apps with MCP.
Deep dive into vector search and storage.
Connecting embeddings to real-world apps.
Implementing long-term memory for agents.
Official interactive course for mastering Claude Code.
NVIDIA's comprehensive AI and deep learning course catalog.
Comprehensive AI and prompt engineering courses by DAIR.AI.