01
AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
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155 plain-English guides, structured learning paths, and an open library — built by an independent 501(c)(3) nonprofit so anyone can understand modern AI.
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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.
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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
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Language AI
Constrained Decoding
Constrained decoding forces a language model to generate output that follows strict rules — like valid JSON, a regex pattern, or a fixed set of choices…
Language AILogit Bias
Logit bias is a knob that nudges a language model toward or away from specific tokens by adding a fixed number to their scores before the model picks…
Language AIKV Cache
The KV cache stores the key and value vectors a transformer has already computed for previous tokens, so it doesn't have to recompute them for every new word…
Language AIJailbreaking and Red-Teaming
Jailbreaking is the practice of crafting prompts that trick an AI model into ignoring its safety rules, while red-teaming is the organized effort to find…
Language AITest-Time Compute Scaling
Test-time compute scaling means giving a model more thinking time and computation when it answers a question, rather than only making it bigger during…
Language AIAgentic Tool Orchestration
Agentic tool orchestration is how an AI model plans and chains together external tools, like search engines, code runners, databases, and APIs, to accomplish…
Language AIHybrid Search
Hybrid search blends keyword matching with semantic vector search so a system catches both exact terms and the meaning behind a query.
Language AIDocument Chunking Strategies
Document chunking is how you split long text into retrievable pieces before embedding it for search or RAG.
Language AILong-Context Modeling
Long-context modeling lets a language model read and reason over very large inputs at once, from hundreds of pages to entire codebases.
Language AIGrounding and Citations
Grounding ties an AI's answers to specific source documents instead of letting it answer from memory alone, and citations show exactly which sources backed…
Language AILLM-as-a-Judge
LLM-as-a-judge uses one language model to score or compare the outputs of another, automating quality evaluation that used to require human raters.
Language AIGuardrails and Output Moderation
Guardrails are the safety checks wrapped around a language model to keep its inputs and outputs within acceptable bounds, blocking harmful, off-topic…
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