Search across educators, skills, and resources.

Swyx

AI Engineer · Intermediate to advanced

A useful hub for the emerging AI engineering stack and practitioner talks.

Skills

AI engineering, Agents, Developer tools

Andrew Ng

DeepLearning.AI Short Courses · Beginner to advanced

Structured, practical courses from prompt engineering through agentic workflows.

Skills

Prompting, Agents, RAG, ML foundations

Rachel Thomas

fast.ai · Beginner to intermediate

Good practical teaching on making ML more understandable and useful.

Skills

Practical ML, Ethics, Education

Simon Willison

Simon Willison on LLMs · Beginner to advanced

Consistently useful notes, demos, model comparisons, and warnings about practical LLM use without product marketing gloss.

Skills

LLM tools, Prompting, AI safety, Local models, Model selection

Jason Liu

Instructor · Intermediate

Practical patterns for getting reliable structured data from LLMs.

Skills

Structured outputs, Extraction, RAG

Elvis Saravia

DAIR.AI Prompt Engineering Guide · Beginner to advanced

A broad prompt engineering guide with many concrete examples and patterns.

Skills

Prompting, RAG, Reasoning, Agents

Jay Alammar

The Illustrated Transformer · Beginner to intermediate

Still one of the clearest visual explanations of transformer concepts.

Skills

Transformers, Embeddings, LLM concepts

Addy Osmani

AI Engineering resources · Beginner to intermediate

Useful for software teams applying AI tools to real engineering work.

Skills

AI coding, Engineering workflows, Frontend

Matt Pocock

AI Hero · Beginner to advanced

Practical developer-focused AI education across LLM fundamentals, AI SDK app development, MCP, Claude Code workflows, agent-ready codebases, evals, TDD, handoffs, and reusable skills such as /teach, /grill-me, /to-prd, /to-issues, /tdd, /triage, and /handoff.

Skills

AI coding, Claude Skills, Agentic workflows, AI SDK, MCP, LLM fundamentals, Personalized learning

Jerry Liu

LlamaIndex · Intermediate

Strong practical material for connecting LLMs to private data, documents, retrieval, and workflows.

Skills

RAG, Agents, Document workflows, Context augmentation

Daniel Bourke

Learn PyTorch · Beginner to intermediate

Hands-on PyTorch learning path that complements fast.ai and model-internals material.

Skills

PyTorch, Deep learning, Computer vision

Patrick Loeber

Python Engineer · Beginner to intermediate

Practical Python tutorials for ML fundamentals, PyTorch, and AI app basics.

Skills

PyTorch, Python ML, LLM apps

Laurence Moroney

AI and Machine Learning for Coders · Beginner to intermediate

Practical developer-oriented teaching for ML foundations and TensorFlow.

Skills

TensorFlow, ML foundations, Computer vision, NLP

François Chollet

Deep Learning with Python · Intermediate

Clear conceptual and practical deep learning education from the creator of Keras.

Skills

Keras, Deep learning, Model design

Aurelien Geron

Hands-On Machine Learning · Beginner to intermediate

One of the most useful hands-on books for classical ML plus neural network foundations.

Skills

Scikit-learn, TensorFlow, ML foundations, Deep learning

Linus Lee

Linus Lee · Intermediate

Useful for people thinking deeply about AI as a medium for tools and interfaces.

Skills

AI interfaces, Personal tools, LLM UX

Lance Martin

LangChain and LangGraph tutorials · Intermediate

Hands-on notebooks for LangGraph, agent patterns, retrieval, and stateful LLM apps.

Skills

LangGraph, Agents, RAG, LLM orchestration

Greg Kamradt

Data Independent AI tutorials · Beginner to intermediate

Practical walkthroughs for retrieval, LLM application patterns, and common developer questions.

Skills

RAG, LLM apps, Prompting, Evaluation

James Briggs

James Briggs AI tutorials · Beginner to intermediate

Useful practical explanations of embeddings, retrieval, LangChain, Pinecone, and agent workflows.

Skills

Vector search, RAG, Agents, Embeddings

Connor Shorten

Weaviate education videos · Beginner to intermediate

Good interviews and tutorials around vector databases, retrieval systems, and AI app patterns.

Skills

Vector search, RAG, Hybrid search, Agents

Nils Reimers

Sentence Transformers · Intermediate

Essential education for understanding sentence embeddings and semantic search in practice.

Skills

Embeddings, Semantic search, Vector search, NLP

Phil Schmid

Hugging Face LLM tutorials · Intermediate to advanced

Hands-on guides for fine-tuning, serving, and using open-source models with Hugging Face tooling.

Skills

Open models, Fine-tuning, Deployment, Transformers

Lewis Tunstall

NLP with Transformers · Intermediate

Strong practical guide to using Transformer models for real NLP tasks.

Skills

Transformers, NLP, Open models, Fine-tuning

Krish Naik

Krish Naik AI tutorials · Beginner to intermediate

Large catalog of practical machine learning, deep learning, and generative AI tutorials.

Skills

Machine learning, Deep learning, LLM apps, MLOps

One of the best free ecosystems for learning open-source AI by building with models, datasets, spaces, agents, context engineering, and MCP workflows.

Topics

Agents, Context engineering, MCP, Transformers, Post-training, Open models

A fast, practical way to build vocabulary and intuition before going deeper into LLMs or AI engineering.

Topics

ML foundations, Classification, Embeddings, Neural networks

Useful when you are ready to build multi-step LLM applications, agents, and graph-based workflows.

Topics

LangGraph, Agents, LLM orchestration, RAG

Good for builders who need to measure, debug, and improve LLM apps rather than just demo them.

Topics

LLM apps, Evals, Experiment tracking, MLOps

Official model and implementation material for learning current GPT-5.5, GPT-5.5 Pro, and GPT-5.4 tradeoffs, Codex workflows, agent evals, MCP and connector patterns, retrieval, model optimization, and structured outputs.

Topics

GPT models, Reasoning models, Model selection, Agents, RAG, Structured outputs, MCP, Evals

A structured lesson path for understanding when to use agents and how to build simple agentic systems.

Topics

Agents, Multi-agent workflows, Tool use

Practical developer tutorials and clear overviews of current AI engineering topics.

Topics

Speech AI, LLMs, Agents, ML concepts

Useful for understanding vector search, embeddings, chunking, retrieval, and RAG system design.

Topics

Vector databases, RAG, Embeddings, Search

Good structured learning around vector databases, retrieval, and search relevance.

Topics

Vector search, RAG, Hybrid search, Embeddings

Useful for Python developers who want clean abstractions around prompts, tools, and model calls.

Topics

LLM app architecture, Prompt engineering, Tool calling

Very practical for regression testing prompts, model changes, and LLM outputs.

Topics

Prompt testing, Evals, Red teaming

Useful structured free courses for the data/ML engineering skills underneath AI products.

Topics

ML engineering, MLOps, Data engineering

A rigorous entry point into classical AI concepts, search, optimization, machine learning, neural networks, and language processing.

Topics

Search, Knowledge representation, ML foundations, AI foundations

A deep route into the NLP concepts behind embeddings, attention, and modern language models.

Topics

NLP, Transformers, Embeddings, Language models

Useful for practical GPU, deep learning, and enterprise AI training with hands-on labs.

Topics

Deep learning, GPU computing, Generative AI, Deployment

Best for people learning AI services, generative AI apps, and ML workflows on AWS.

Topics

Cloud AI, Agents, MLOps, Generative AI

Hands-on labs for people building AI systems on Google Cloud and Vertex AI.

Topics

Cloud AI, Vertex AI, Generative AI, MLOps

Useful for Azure AI services, Copilot extensibility, and Microsoft-focused AI app development.

Topics

Azure AI, Agents, Copilot, Cloud AI

Large library of practical tutorials for developers who prefer project-based learning.

Topics

Python, Machine learning, LLM apps, Coding with AI

Good for beginners who want guided coding exercises while learning AI concepts.

Topics

AI foundations, Python, Prompting, LLM apps

Developer-focused material for using Stable Diffusion and Stability APIs.

Topics

Image generation, API workflows, Creative AI

Fast route to test many hosted AI models without managing infrastructure.

Topics

Model APIs, Prototyping, Image generation, LLM apps

Useful for learning how to run AI workloads, inference jobs, and GPU tasks in production-like environments.

Topics

Deployment, GPU workloads, AI engineering, Batch jobs

Good for vector search concepts and practical retrieval implementation.

Topics

Vector search, RAG, Embeddings, Search

Workflow skill catalog

AI Skills for Real Engineers

Matt Pocock / AI Hero · Skill catalog

Use this when you want opinionated coding-agent workflows instead of generic prompt snippets.

Start

Start with /teach, /grill-me, /to-prd, /to-issues, /tdd, /triage, or /handoff depending on the job.