01
AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Free AI library
Technical guidesFree forever.
177 plain-English guides, structured learning paths, and an open library — built by an independent 501(c)(3) nonprofit so anyone can understand modern AI.
177Free guides
1Topic tracks
~2 minPer guide
~6hReading time
Start here
Five outcome-based courses
Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
02
Responsible AI User
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
03
AI at Work
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
04
AI Policy & Society
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
05
Building with AI Systems
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
Topic tracks
Browse by track
Jump into the area you care about. Every track has multiple plain-English guides.
FundamentalsCore concepts: how AI works at a high level.84 guides Language AILLMs, NLP, ChatGPT, prompting, and text understanding.155 guides Visual AIImage generation, computer vision, video, and design.133 guides Audio AIVoice, music, podcasting, and audio-first AI.117 guides CompaniesProfiles of OpenAI, Anthropic, Google, Meta, and more.121 guides ApplicationsHow AI shows up in coding, search, agents, and daily life.111 guides IndustriesAI in healthcare, finance, education, energy, and more.91 guides TechnicalChips, fine-tuning, RAG, vectors, and AI infrastructure.177 guides SocietyBias, privacy, copyright, safety, and the AI future.30 guides
Full library
All guides
177 of 1019 guides shown. Filter by track or search above.
Technical
AI Benchmarks
An AI benchmark is a defined set of tasks, data, and scoring rules used to compare systems.
TechnicalAI Chips & Hardware
AI hardware executes the numerical operations used to train and run models.
TechnicalReinforcement Learning
Reinforcement learning trains an agent to choose actions using feedback about their consequences.
TechnicalAI & Robotics
AI and robotics combine perception, planning, control, and physical action.
TechnicalFine-Tuning
Fine-tuning continues training an existing model on a selected dataset or objective.
TechnicalRetrieval-Augmented Generation (RAG)
Retrieval-augmented generation, or RAG, supplies retrieved material to a generative model when answering a request.
TechnicalVector Databases
A vector database stores numerical representations and retrieves records using a similarity measure, often alongside metadata filters.
TechnicalEdge AI
Edge AI runs model processing close to where data is collected or used, such as on a phone, camera, vehicle, or local gateway.
TechnicalQuantum AI
Quantum AI describes intersections between quantum computing and machine learning, such as using quantum circuits in learning algorithms or using machine…
TechnicalAI Observability
AI observability uses measurements and records to understand how an AI application behaves.
TechnicalAI Model Monitoring
Model monitoring checks whether a deployed model and its inputs continue to behave as expected.
TechnicalAI Inference Optimization
Inference optimization reduces the resources or time required to run a model while preserving the quality needed for its task.
Finished reading? Prove it.
Check what you learned with topic quizzes, then explore our structured courses and current certification requirements. Core guides remain free to read.