Curated video tutorials, playlists, and courses to help you master AI development.
Learn the basics of AI engineering and how to get started with building AI applications. Covers neural network fundamentals from first principles.
3Blue1Brown's visual explanation of gradient descent — the core algorithm powering all neural network training. Essential before diving into LLM fine-tuning or training.
Understanding the Transformer architecture that powers every modern LLM — GPT-4, Claude, Gemini. Covers self-attention, multi-head attention, and positional encoding.
Andrej Karpathy's landmark 2023 talk on the fundamentals of LLMs. Covers the GPT architecture, RLHF training pipeline, prompt injection, fine-tuning strategies, and how modern AI systems are built and deployed at scale.
The definitive hands-on tutorial by Andrej Karpathy. Build a GPT language model from scratch using Python and PyTorch, implementing every component — tokenization, embeddings, multi-head attention, and training. 2 hours of pure deep learning.
Andrej Karpathy's complete course on building neural networks from scratch. Starts with backpropagation basics (micrograd), then builds up through MLP, WaveNet, and full transformer language models. The most thorough practical ML course on the internet.
Andrej Karpathy's definitive Microsoft Build 2023 keynote on the state of GPT models. Covers the complete ChatGPT training pipeline, fine-tuning strategies, prompt engineering, and practical advice for building production AI applications.
3Blue1Brown's crystal-clear visual explanation of backpropagation — the algorithm that makes neural network training possible. Essential for understanding how LLMs learn from data.
Andrej Karpathy trains GPT-2 from scratch live on screen using modern techniques. Covers FP16 training, Flash Attention, gradient clipping, cosine learning rate schedules, and deploying to cloud GPUs — real-world LLM training from beginning to end.
Comprehensive tutorial on LangChain. Learn to build RAG pipelines, conversational AI, autonomous agents, and production LLM applications using Python. Covers chains, memory, tools, and vector databases end-to-end.
Learn how to build production-ready Retrieval Augmented Generation (RAG) systems that let LLMs answer questions based on your own documents, codebase, or knowledge base. Covers embeddings, vector databases (Chroma, Pinecone), chunking strategies, and query optimization.
Complete guide to running powerful AI models — Llama 3, DeepSeek, Mistral, Phi-4 — on your own hardware using Ollama. Covers installation on Mac/Windows/Linux, model management, performance tuning, and integrating local models with VS Code extensions like Continue.
Learn to use the OpenAI API from scratch. Covers text completions, function calling, embeddings, streaming responses, image generation with DALL-E, and speech-to-text with Whisper. Build three real projects by the end.
Master Cursor AI IDE with this comprehensive 2026 tutorial. Learn Composer mode for multi-file editing, the powerful Tab autocomplete, codebase indexing, custom AI rules (.cursorrules), and the fastest keyboard shortcuts. Includes a real project walkthrough.
Learn to use GitHub Copilot at an expert level. Covers inline suggestions, Copilot Chat, writing effective comment-driven prompts, ghost text patterns, slash commands in the IDE, and how to build a full feature using only Copilot.
Complete guide to building web apps with Next.js 14, covering Server Components, Server Actions, App Router, and modern full-stack patterns.
Introduction to Next.js 14 and how to set up your development environment with the App Router and TypeScript.
Comprehensive Python course for AI/ML engineering. Covers Python fundamentals, data manipulation with NumPy and Pandas, working with real AI APIs, and building three hands-on AI-powered projects from start to finish.